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5.0.0

We are very excited to announce NLU 5.0.0 has been released!

It comes with `ZeroShotClassification` models based on `Bert`, `DistilBert`, and `Roberta` architectures.
Additionally Medical Text Generator based on `Bio-GPT` as-well as a `Bart` based General Text Generator are now available in NLU.
Finally, `ConvNextForImageClassification` is an image classifier based on ConvNet models.




------

ConvNextForImageClassification
[Tutorial Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/image_classification/convnext_image_classification_overview.ipynb)
`ConvNextForImageClassification` is an image classifier based on ConvNet models.
The ConvNeXT model was proposed in A ConvNet for the 2020s by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie. ConvNeXT is a pure convolutional model (ConvNet), inspired by the design of Vision Transformers, that claims to outperform them.
Powered by [ConvNextForImageClassification](https://sparknlp.org/docs/en/transformers#convnextforimageclassification)
Reference: [A ConvNet for the 2020s](https://arxiv.org/abs/2201.03545)

New NLU Models:

| Language | NLU Reference | Spark NLP Reference | Task | Annotator Class |
|:-----------|:----------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------|:---------------------|:------------------------|
| en | [en.classify_image.convnext.tiny](https://nlp.johnsnowlabs.com/2023/03/28/image_classifier_convnext_tiny_224_local_en.html) | [image_classifier_convnext_tiny_224_local](https://nlp.johnsnowlabs.com/2023/03/28/image_classifier_convnext_tiny_224_local_en.html) | Image Classification | ConvNextImageClassifier |
| en | [en.classify_image.convnext.tiny](https://nlp.johnsnowlabs.com/2023/07/05/image_classifier_convnext_tiny_224_local_en.html) | [image_classifier_convnext_tiny_224_local](https://nlp.johnsnowlabs.com/2023/07/05/image_classifier_convnext_tiny_224_local_en.html) | Image Classification | ConvNextImageClassifier |

------


DistilBertForZeroShotClassification
[Tutorial Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/classifiers/Distilbert_Zero_Shot_Classifier.ipynb)

`DistilBertForZeroShotClassification` using a ModelForSequenceClassification trained on NLI (natural language inference) tasks.
Any combination of sequences and labels can be passed and each combination will be posed as a premise/hypothesis pair and passed to the pretrained model.
Powered by [DistilBertForZeroShotClassification](https://sparknlp.org/docs/en/transformers#distilbertforzeroshotclassification)

New NLU Models:

| Language | NLU Reference | Spark NLP Reference | Task | Annotator Class |
|:-----------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------|:------------------------------------|
| en | [en.distilbert.zero_shot_classifier](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_uncased_mnli_en.html) | [distilbert_base_zero_shot_classifier_uncased_mnli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_uncased_mnli_en.html) | Zero-Shot Classification | DistilBertForZeroShotClassification |
| tr | [tr.distilbert.zero_shot_classifier.multinli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr.html) | [distilbert_base_zero_shot_classifier_turkish_cased_multinli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr.html) | Zero-Shot Classification | DistilBertForZeroShotClassification |
| tr | [tr.distilbert.zero_shot_classifier.allnli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_turkish_cased_allnli_tr.html) | [distilbert_base_zero_shot_classifier_turkish_cased_allnli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_turkish_cased_allnli_tr.html) | Zero-Shot Classification | DistilBertForZeroShotClassification |
| tr | [tr.distilbert.zero_shot_classifier.snli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_turkish_cased_snli_tr.html) | [distilbert_base_zero_shot_classifier_turkish_cased_snli](https://nlp.johnsnowlabs.com/2023/04/20/distilbert_base_zero_shot_classifier_turkish_cased_snli_tr.html) | Zero-Shot Classification | DistilBertForZeroShotClassification |

------

BertForZeroShotClassification
[Tutorial Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/classifiers/Bert_Zero_Shot_Classifier.ipynb)
`BertForZeroShotClassification` using a ModelForSequenceClassification trained on NLI (natural language inference) tasks.
Any combination of sequences and labels can be passed and each combination will be posed as a premise/hypothesis pair and passed to the pretrained model.
Powered by [BertForZeroShotClassification](https://sparknlp.org/docs/en/transformers#bertforzeroshotclassification)

New NLU Models:

| Language | NLU Reference | Spark NLP Reference | Task | Annotator Class |
|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------|:-------------------------|:------------------------------|
| en | [en.bert.zero_shot_classifier](https://nlp.johnsnowlabs.com/2023/04/05/bert_base_cased_zero_shot_classifier_xnli_en.html) | [bert_base_cased_zero_shot_classifier_xnli](https://nlp.johnsnowlabs.com/2023/04/05/bert_base_cased_zero_shot_classifier_xnli_en.html) | Zero-Shot Classification | BertForZeroShotClassification |

------

RoBertaForZeroShotClassification
[Tutorial Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/classifiers/Roberta_Zero_Shot_Classifier.ipynb)
`RoBertaForZeroShotClassification` using a ModelForSequenceClassification trained on NLI (natural language inference) tasks.
Any combination of sequences and labels can be passed and each combination will be posed as a premise/hypothesis pair and passed to the pretrained model.
Powered by [RoBertaForZeroShotClassification](https://sparknlp.org/docs/en/transformers#robertaforzeroshotclassification)

New NLU Models:

| Language | NLU Reference | Spark NLP Reference | Task | Annotator Class |
|:-----------|:-------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------|:-------------------------|:---------------------------------|
| en | [en.roberta.zero_shot_classifier](https://nlp.johnsnowlabs.com/2023/05/04/roberta_base_zero_shot_classifier_nli_en.html) | [roberta_base_zero_shot_classifier_nli](https://nlp.johnsnowlabs.com/2023/05/04/roberta_base_zero_shot_classifier_nli_en.html) | Zero-Shot Classification | RoBertaForZeroShotClassification |


------

BartTransformer
[Tutorial Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/sequence2sequence/bart_transformer.ipynb)

The Facebook `BART (Bidirectional and Auto-Regressive Transformer)` model is a state-of-the-art language generation model that was introduced by Facebook AI in 2019. It is based on the transformer architecture and is designed to handle a wide range of natural language processing tasks such as text generation, summarization, and machine translation.
BART is unique in that it is both bidirectional and auto-regressive, meaning that it can generate text both from left-to-right and from right-to-left. This allows it to capture contextual information from both past and future tokens in a sentence,resulting in more accurate and natural language generation.
The model was trained on a large corpus of text data using a combination of unsupervised and supervised learning techniques. It incorporates pretraining and fine-tuning phases, where the model is first trained on a large unlabeled corpus of text, and then fine-tuned on specific downstream tasks.
BART has achieved state-of-the-art performance on a wide range of NLP tasks, including summarization, question-answering, and language translation. Its ability to handle multiple tasks and its high performance on each of these tasks make it a versatile and valuable tool for natural language processing applications.
Powered by [BartTransformer](https://sparknlp.org/docs/en/transformers#barttransformer)
Reference : [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://aclanthology.org/2020.acl-main.703.pdf)

New NLU Models:

| Language | NLU Reference | Spark NLP Reference | Task | Annotator Class |
|:-----------|:--------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------|:--------------|:------------------|
| en | [en.seq2seq.distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/04/07/distilbart_xsum_12_6_en.html) | [distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/04/07/distilbart_xsum_12_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/04/09/distilbart_xsum_12_6_en.html) | [distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/04/09/distilbart_xsum_12_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_xsum_12_6_en.html) | [distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_xsum_12_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_xsum_12_6_en.html) | [distilbart_xsum_12_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_xsum_12_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.bart_large_cnn](https://nlp.johnsnowlabs.com/2023/04/09/bart_large_cnn_en.html) | [bart_large_cnn](https://nlp.johnsnowlabs.com/2023/04/09/bart_large_cnn_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.bart_large_cnn](https://nlp.johnsnowlabs.com/2023/05/09/bart_large_cnn_en.html) | [bart_large_cnn](https://nlp.johnsnowlabs.com/2023/05/09/bart_large_cnn_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.bart_large_cnn](https://nlp.johnsnowlabs.com/2023/05/11/bart_large_cnn_en.html) | [bart_large_cnn](https://nlp.johnsnowlabs.com/2023/05/11/bart_large_cnn_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_cnn_6_6](https://nlp.johnsnowlabs.com/2023/04/09/distilbart_cnn_6_6_en.html) | [distilbart_cnn_6_6](https://nlp.johnsnowlabs.com/2023/04/09/distilbart_cnn_6_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_cnn_6_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_cnn_6_6_en.html) | [distilbart_cnn_6_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_cnn_6_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_cnn_6_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_cnn_6_6_en.html) | [distilbart_cnn_6_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_cnn_6_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_cnn_12_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_cnn_12_6_en.html) | [distilbart_cnn_12_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_cnn_12_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_cnn_12_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_cnn_12_6_en.html) | [distilbart_cnn_12_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_cnn_12_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_xsum_6_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_xsum_6_6_en.html) | [distilbart_xsum_6_6](https://nlp.johnsnowlabs.com/2023/05/09/distilbart_xsum_6_6_en.html) | Summarization | BartTransformer |
| en | [en.seq2seq.distilbart_xsum_6_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_xsum_6_6_en.html) | [distilbart_xsum_6_6](https://nlp.johnsnowlabs.com/2023/05/11/distilbart_xsum_6_6_en.html) | Summarization | BartTransformer |


------


MedicalTextGenerator
[Tutorial Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/healthcare/sequence2sequence/NLU_Medical_TextGenerators.ipynb)

`MedicalTextGenerator` uses the basic BioGPT model to perform various tasks related to medical text abstraction.
A user can provide a prompt and context and instruct the system to perform a specific task, such as explaining why a patient may have a particular disease or paraphrasing the context more directly.
In addition, this annotator can create a clinical note for a cancer patient using the given keywords or write medical texts based on introductory sentences.
The BioGPT model is trained on large volumes of medical data allowing it to identify and extract the most relevant information from the text provided.
Powered by [TextGenerator](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators#textgenerator)

New NLU Models:

| Language | NLU Reference | Spark NLP Reference | Task | Annotator Class |
|:-----------|:-----------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------|:----------------|:---------------------|
| en | [en.generate.biomedical_biogpt_base](https://nlp.johnsnowlabs.com/2023/04/03/text_generator_biomedical_biogpt_base_en.html) | [text_generator_biomedical_biogpt_base](https://nlp.johnsnowlabs.com/2023/04/03/text_generator_biomedical_biogpt_base_en.html) | Text Generation | MedicalTextGenerator |
| en | [en.generate.generic_flan_base](https://nlp.johnsnowlabs.com/2023/04/03/text_generator_generic_flan_base_en.html) | [text_generator_generic_flan_base](https://nlp.johnsnowlabs.com/2023/04/03/text_generator_generic_flan_base_en.html) | Text Generation | MedicalTextGenerator |
| en | [en.generate.generic_jsl_base](https://nlp.johnsnowlabs.com/2023/04/03/text_generator_generic_jsl_base_en.html) | [text_generator_generic_jsl_base](https://nlp.johnsnowlabs.com/2023/04/03/text_generator_generic_jsl_base_en.html) | Text Generation | MedicalTextGenerator |
| en | [en.generate.generic_flan_t5_large](https://nlp.johnsnowlabs.com/2023/04/04/text_generator_generic_flan_t5_large_en.html) | [text_generator_generic_flan_t5_large](https://nlp.johnsnowlabs.com/2023/04/04/text_generator_generic_flan_t5_large_en.html) | Text Generation | MedicalTextGenerator |
| en | [en.generate.biogpt_chat_jsl](https://nlp.johnsnowlabs.com/2023/04/12/biogpt_chat_jsl_en.html) | [biogpt_chat_jsl](https://nlp.johnsnowlabs.com/2023/04/12/biogpt_chat_jsl_en.html) | Text Generation | MedicalTextGenerator |
| en | [en.generate.biogpt_chat_jsl_conversational](https://nlp.johnsnowlabs.com/2023/04/18/biogpt_chat_jsl_conversational_en.html) | [biogpt_chat_jsl_conversational](https://nlp.johnsnowlabs.com/2023/04/18/biogpt_chat_jsl_conversational_en.html) | Text Generation | MedicalTextGenerator |
| en | [en.generate.biogpt_chat_jsl_conditions](https://nlp.johnsnowlabs.com/2023/05/11/biogpt_chat_jsl_conditions_en.html) | [biogpt_chat_jsl_conditions](https://nlp.johnsnowlabs.com/2023/05/11/biogpt_chat_jsl_conditions_en.html) | Text Generation | MedicalTextGenerator |



------

Install NLU

python
pip install nlu pyspark



Additional NLU resources
* [140+ NLU Tutorials](https://nlu.johnsnowlabs.com/docs/en/notebooks)
* [NLU in Action](https://nlp.johnsnowlabs.com/demo)
* [Streamlit visualizations docs](https://nlu.johnsnowlabs.com/docs/en/streamlit_viz_examples)
* The complete list of all 20000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models).
* [Spark NLP publications](https://medium.com/spark-nlp)
* [NLU documentation](https://nlu.johnsnowlabs.com/docs/en/install)
* [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU!



422
New Medical Summarizers:
- 'en.summarize.clinical_jsl'
- 'en.summarize.clinical_jsl_augmented'
- 'en.summarize.biomedical_pubmed'
- 'en.summarize.generic_jsl'
- 'en.summarize.clinical_questions'
- 'en.summarize.radiology'
- 'en.summarize.clinical_guidelines_large'
- 'en.summarize.clinical_laymen'

421
Bugfixes for saving and reloading pipelines on databricks

4.9

4.7

4.6

| 5 | 3.6 | 1.4 | 0.2 | setosa |

4.2.0

Support for Speech2Text, Images-Classification, Tabular Data, Zero-Shot-NER, via Wav2Vec2, Tapas, VIT , 4000+ New Models, 90+ Languages, in John Snow Labs NLU 4.2.0


We are incredibly excited to announce NLU 4.2.0 has been released with new 4000+ models in 90+ languages and support for new 8 Deep Learning Architectures.
4 new tasks are included for the very first time,
**Zero-Shot-NER**, **Automatic Speech Recognition**, **Image Classification** and **Table Question Answering** powered
by [Wav2Vec 2.0](https://arxiv.org/pdf/2006.11477.pdf), [HuBERT](https://arxiv.org/abs/2106.07447), [TAPAS](https://aclanthology.org/2020.acl-main.398.pdf), [VIT](https://arxiv.org/pdf/2010.11929.pdf), [SWIN](https://arxiv.org/abs/2103.14030), [Zero-Shot-NER](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators#zeroshotnermodel).

Additionally, [CamemBERT](https://arxiv.org/abs/1911.03894) based architectures are available for Sequence and Token Classification powered by Spark-NLPs
[CamemBertForSequenceClassification](https://nlp.johnsnowlabs.com/docs/en/transformers#camembertforsequenceclassification) and [CamemBertForTokenClassification](https://nlp.johnsnowlabs.com/docs/en/transformers#camembertfortokenclassification)

Automatic Speech Recognition (ASR)
[Demo Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/automatic_speech_recognition/automatic_speech_recognition_overview_ASR.ipynb)
[Wav2Vec 2.0](https://arxiv.org/pdf/2006.11477.pdf) and [HuBERT](https://arxiv.org/abs/2106.07447) enable ASR for the very first time in NLU.
**Wav2Vec2** is a transformer model for speech recognition that uses unsupervised pre-training on large amounts of unlabeled speech data to improve the accuracy of automatic speech recognition (ASR) systems. It is based on a self-supervised learning approach that learns to predict masked portions of speech signal, and has shown promising results in reducing the amount of labeled training data required for ASR tasks.

These Models are powered by Spark-NLP's [Wav2Vec2ForCTC Annotator](https://nlp.johnsnowlabs.com/docs/en/transformers#wav2vec2forctc)
![Wav2Vec2](https://user-images.githubusercontent.com/5762953/192140859-f165317e-4a8f-4b32-9d11-6063db19c503.png)

**HuBERT** models match or surpass the SOTA approaches for speech representation learning for speech recognition, generation, and compression. The Hidden-Unit BERT (HuBERT) approach was proposed for self-supervised speech representation learning, which utilizes an offline clustering step to provide aligned target labels for a BERT-like prediction loss.

These Models is powered by Spark-NLP's [HubertForCTC Annotator](https://nlp.johnsnowlabs.com/docs/en/transformers#hubertforctc)

![HUBERT](https://user-images.githubusercontent.com/5762953/217865459-375756c3-a110-4917-8319-1deecb55304d.png)

**Usage**

You just need an audio-file on disk and pass the path to it or a folder of audio-files.

python
import nlu
Let's download an audio file
!wget https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/audio/samples/wavs/ngm_12484_01067234848.wav
Let's listen to it
from IPython.display import Audio
FILE_PATH = "ngm_12484_01067234848.wav"
asr_df = nlu.load('en.speech2text.wav2vec2.v2_base_960h').predict('ngm_12484_01067234848.wav')
asr_df


| text |
|:---------------------------------------------|
| PEOPLE WHO DIED WHILE LIVING IN OTHER PLACES |



To test out **HuBERT** you just need to update the parameter for `load()`
python
asr_df = nlu.load('en.speech2text.hubert').predict('ngm_12484_01067234848.wav')
asr_df



Image Classification
[Demo Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/image_classification/image_classification_overview.ipynb)

For the first time ever NLU introduces state-of-the-art image classifiers based on
[VIT](https://arxiv.org/pdf/2010.11929.pdf) and [Swin](https://arxiv.org/abs/2103.14030) giving you access to hundreds of image classifiers for various domains.

Inspired by the Transformer scaling successes in NLP, the researchers experimented with applying a standard Transformer directly to images, with the fewest possible modifications. To do so, images are split into patches and the sequence of linear embeddings of these patches were provided as an input to a Transformer. Image patches were actually treated the same way as tokens (words) in an NLP application. Image classification models were trained in supervised fashion.

You can check [Scale Vision Transformers (ViT) Beyond Hugging Face](https://hackernoon.com/scale-vision-transformers-vit-beyond-hugging-face) article to learn deeper how ViT works and how it is implemeted in Spark NLP.
This is Powerd by Spark-NLP's [VitForImageClassification Annotator](https://nlp.johnsnowlabs.com/docs/en/transformers#vitforimageclassification)

![VIT](https://camo.githubusercontent.com/b27f01b616e81636a6135573bbf37a006619ab0853f7dd55ea4fb0e9e89dd33d/68747470733a2f2f692e696d6775722e636f6d2f676e31736369742e706e67)


Swin is a hierarchical Transformer whose representation is computed with Shifted windows.
The shifted windowing scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while also allowing for cross-window connection.
This hierarchical architecture has the flexibility to model at various scales and has linear computational complexity with respect to image size. These qualities of Swin Transformer make it compatible with a broad range of vision tasks
This is powerd by Spark-NLP's [Swin For Image Classification](https://nlp.johnsnowlabs.com/docs/en/transformers#swinforimageclassification)
[Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) by Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo.

![swin](https://user-images.githubusercontent.com/5762953/217882453-bfc4d585-f21b-4401-bdcb-14788973c159.png)

**Usage:**
python
Download an image
os.system('wget https://raw.githubusercontent.com/JohnSnowLabs/nlu/release/4.2.0/tests/datasets/ocr/vit/ox.jpg')
Load VIT model and predict on image file
vit = nlu.load('en.classify_image.base_patch16_224').predict('ox.jpg')


Lets download a folder of images and predict on it
python
!wget -q https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/images/images.zip
import shutil
shutil.unpack_archive("images.zip", "images", "zip")
! ls /content/images/images/


Once we have image data its easy to label it, we just pass the folder with images to nlu.predict()
and NLU will return a pandas DF with one row per image detected
python
nlu.load('en.classify_image.base_patch16_224').predict('/content/images/images')



![image_classification 1.png](https://raw.githubusercontent.com/JohnSnowLabs/nlu/master/docs/assets/images/releases/4_2_0/image_classification.png)


To use **SWIN** we just update the parameter to `load()`
python
load('en.classify_image.swin.tiny').predict('/content/images/images')


-----------


Visual Table Question Answering
TapasForQuestionAnswering can load TAPAS Models with a cell selection head and optional aggregation head on top for question-answering tasks on tables (linear layers on top of the hidden-states output to compute logits and optional logits_aggregation), e.g. for SQA, WTQ or WikiSQL-supervised tasks. TAPAS is a BERT-based model specifically designed (and pre-trained) for answering questions about tabular data.

[Demo Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/table_question_answering/table_question_answering_with_tapas.ipynb)

Powered by [TAPAS: Weakly Supervised Table Parsing via Pre-training](https://aclanthology.org/2020.acl-main.398.pdf)
![TAPAS](https://user-images.githubusercontent.com/5762953/192140733-e08a1e99-0aee-455d-af29-73af497a03ef.png)

**Usage:**

First we need a pandas dataframe on for which we want to ask questions. The so called "context"
python
import pandas as pd

context_df = pd.DataFrame({
'name':['Donald Trump','Elon Musk'],
'money': ['$100,000,000','$20,000,000,000,000'],
'married': ['yes','no'],
'age' : ['75','55'] })
context_df



Then we create an array of questions
python
questions = [
"Who earns less than 200,000,000?",
"Who earns more than 200,000,000?",
"Who earns 100,000,000?",
"How much money has Donald Trump?",
"Who is the youngest?",
]
questions



Now Combine the data, pass it to NLU and get answers for your questions
python
import nlu
Now we combine both to a tuple and we are done! We can now pass this to the .predict() method
tapas_data = (context_df, questions)
Lets load a TAPAS QA model and predict on (context,question).
It will give us an aswer for every question in the questions array, based on the context in context_df
answers = nlu.load('en.answer_question.tapas.wtq.large_finetuned').predict(tapas_data)
answers


| sentence | tapas_qa_UNIQUE_aggregation | tapas_qa_UNIQUE_answer | tapas_qa_UNIQUE_cell_positions | tapas_qa_UNIQUE_cell_scores | tapas_qa_UNIQUE_origin_question |
|:---------------------------------|:------------------------------|:-------------------------|:---------------------------------|------------------------------:|:----------------------------------|
| Who earns less than 200,000,000? | NONE | Donald Trump | [0, 0] | 1 | Who earns less than 200,000,000? |
| Who earns more than 200,000,000? | NONE | Elon Musk | [0, 1] | 1 | Who earns more than 200,000,000? |
| Who earns 100,000,000? | NONE | Donald Trump | [0, 0] | 1 | Who earns 100,000,000? |
| How much money has Donald Trump? | SUM | SUM($100,000,000) | [1, 0] | 1 | How much money has Donald Trump? |
| Who is the youngest? | NONE | Elon Musk | [0, 1] | 1 | Who is the youngest? |


-----

Zero-Shot NER

[Demo Notebook](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/healthcare/medical_named_entity_recognition/zero_shot_ner.ipynb)
Based on John Snow Labs Enterprise-NLP [ZeroShotNerModel](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators#zeroshotnermodel)
This architecture is based on `RoBertaForQuestionAnswering`.
Zero shot models excel at generalization, meaning that the model can accurately predict entities in very different data sets without the need to fine tune the model or train from scratch for each different domain.
Even though a model trained to solve a specific problem can achieve better accuracy than a zero-shot model in this specific task,
it probably won’t be be useful in a different task.
That is where zero-shot models shows its usefulness by being able to achieve good results in various domains.

**Usage:**

We just need to load the zero-shot NER model and configure a set of entity definitions.
python
import nlu
load zero-shot ner model
enterprise_zero_shot_ner = nlu.load('en.zero_shot.ner_roberta')

Configure entity definitions
enterprise_zero_shot_ner['zero_shot_ner'].setEntityDefinitions(
{
"PROBLEM": [
"What is the disease?",
"What is his symptom?",
"What is her disease?",
"What is his disease?",
"What is the problem?",
"What does a patient suffer",
"What was the reason that the patient is admitted to the clinic?",
],
"DRUG": [
"Which drug?",
"Which is the drug?",
"What is the drug?",
"Which drug does he use?",
"Which drug does she use?",
"Which drug do I use?",
"Which drug is prescribed for a symptom?",
],
"ADMISSION_DATE": ["When did patient admitted to a clinic?"],
"PATIENT_AGE": [
"How old is the patient?",
"What is the gae of the patient?",
],
}
)



Then we can already use this pipeline to predict labels
python
Predict entities
df = enterprise_zero_shot_ner.predict(
[
"The doctor pescribed Majezik for my severe headache.",
"The patient was admitted to the hospital for his colon cancer.",
"27 years old patient was admitted to clinic on Sep 1st by Dr."+
"X for a right-sided pleural effusion for thoracentesis.",
]
)
df


| document | entities_zero_shot | entities_zero_shot_class | entities_zero_shot_confidence | entities_zero_shot_origin_chunk | entities_zero_shot_origin_sentence |
|:----------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------|:---------------------------|--------------------------------:|----------------------------------:|-------------------------------------:|
| The doctor pescribed Majezik for my severe headache. | Majezik | DRUG | 0.646716 | 0 | 0 |
| The doctor pescribed Majezik for my severe headache. | severe headache | PROBLEM | 0.552635 | 1 | 0 |
| The patient was admitted to the hospital for his colon cancer. | colon cancer | PROBLEM | 0.88985 | 0 | 0 |
| 27 years old patient was admitted to clinic on Sep 1st by Dr. X for a right-sided pleural effusion for thoracentesis. | 27 years old | PATIENT_AGE | 0.694308 | 0 | 0 |
| 27 years old patient was admitted to clinic on Sep 1st by Dr. X for a right-sided pleural effusion for thoracentesis. | Sep 1st | ADMISSION_DATE | 0.956461 | 1 | 0 |
| 27 years old patient was admitted to clinic on Sep 1st by Dr. X for a right-sided pleural effusion for thoracentesis. | a right-sided pleural effusion for thoracentesis | PROBLEM | 0.500266 | 2 | 0 |

------

New Notebooks
- [Image Classification with VIT and Swin](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/image_classification/image_classification_overview.ipynb)
- [Zero-Shot-NER](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/healthcare/medical_named_entity_recognition/zero_shot_ner.ipynb)
- [Table Question Answering with TAPAS](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/table_question_answering/table_question_answering_with_tapas.ipynb)
- [Automatic Speech Recognition with Wav2Vec2 and HuBERT ](https://github.com/JohnSnowLabs/nlu/blob/master/examples/colab/component_examples/automatic_speech_recognition/automatic_speech_recognition_overview_ASR.ipynb)




New Models Overview

Supported Languages are:
`ab`, `am`, `ar`, `ba`, `bem`, `bg`, `bn`, `ca`, `co`, `cs`, `da`, `de`, `dv`, `el`, `en`, `es`, `et`, `eu`, `fa`, `fi`, `fon`, `fr`, `fy`, `ga`, `gam`, `gl`, `gu`, `ha`, `he`, `hi`, `hr`, `hu`, `id`, `ig`, `is`, `it`, `ja`, `jv`, `kin`, `kn`, `ko`, `kr`, `ku`, `ky`, `la`, `lg`, `lo`, `lt`, `lu`, `luo`, `lv`, `lwt`, `ml`, `mn`, `mr`, `ms`, `mt`, `nb`, `nl`, `no`, `pcm`, `pl`, `pt`, `ro`, `ru`, `rw`, `sg`, `si`, `sk`, `sl`, `sq`, `st`, `su`, `sv`, `sw`, `swa`, `ta`, `te`, `th`, `ti`, `tl`, `tn`, `tr`, `tt`, `tw`, `uk`, `unk`, `ur`, `uz`, `vi`, `wo`, `xx`, `yo`, `yue`, `zh`, `zu`



Automatic Speech Recognition Models Overview


| Language | NLU Reference | Spark NLP Reference | Annotator Class |
|:---------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------|
| ab | [ab.speech2text.wav2vec_xlsr.gpu.by_hf_test](https://nlp.johnsnowlabs.com/2022/09/26/asr_xls_r_ab_test_by_hf_test_gpu_ab.html) | [asr_xls_r_ab_test_by_hf_test_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_xls_r_ab_test_by_hf_test_gpu_ab.html) | Wav2Vec2ForCTC |
| ba | [ba.speech2text.wav2vec_xlsr.v2_large_300m_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xls_r_300m_bashkir_cv7_opt_gpu_ba.html) | [asr_wav2vec2_large_xls_r_300m_bashkir_cv7_opt_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xls_r_300m_bashkir_cv7_opt_gpu_ba.html) | Wav2Vec2ForCTC |
| bem | [bem.speech2text.wav2vec_xlsr.v2_large_gpu.by_csikasote](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_bemba_gpu_bem.html) | [asr_wav2vec2_large_xlsr_bemba_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_bemba_gpu_bem.html) | Wav2Vec2ForCTC |
| bg | [bg.speech2text.wav2vec_xlsr.v2_large_300m_d2_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xls_r_300m_d2_gpu_bg.html) | [asr_wav2vec2_large_xls_r_300m_d2_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xls_r_300m_d2_gpu_bg.html) | Wav2Vec2ForCTC |
| ca | [ca.speech2text.wav2vec2.voxpopuli.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_100k_voxpopuli_catala_by_ccoreilly_gpu_ca.html) | [asr_wav2vec2_large_100k_voxpopuli_catala_by_ccoreilly_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_100k_voxpopuli_catala_by_ccoreilly_gpu_ca.html) | Wav2Vec2ForCTC |
| cs | [cs.speech2text.wav2vec_xlsr.v2_large.by_arampacha](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_czech_cs.html) | [asr_wav2vec2_large_xlsr_czech](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_czech_cs.html) | Wav2Vec2ForCTC |
| da | [da.speech2text.wav2vec2.v2_base](https://nlp.johnsnowlabs.com/2022/09/25/asr_alvenir_wav2vec2_base_nst_cv9_da.html) | [asr_alvenir_wav2vec2_base_nst_cv9](https://nlp.johnsnowlabs.com/2022/09/25/asr_alvenir_wav2vec2_base_nst_cv9_da.html) | Wav2Vec2ForCTC |
| de | [de.speech2text.wav2vec_xlsr.v3_large.by_marcel](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_german_demo_de.html) | [asr_wav2vec2_large_xlsr_german_demo](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_german_demo_de.html) | Wav2Vec2ForCTC |
| el | [el.speech2text.wav2vec_xlsr.v3_large_gpu.by_skylord](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_greek_2_gpu_el.html) | [asr_wav2vec2_large_xlsr_greek_2_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_greek_2_gpu_el.html) | Wav2Vec2ForCTC |
| en | [en.speech2text.wav2vec_xlsr.v2gpu.by_bakhtullah123](https://nlp.johnsnowlabs.com/2022/09/25/asr_xlsr_training_gpu_en.html) | [asr_xlsr_training_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_xlsr_training_gpu_en.html) | Wav2Vec2ForCTC |
| fa | [fa.speech2text.wav2vec2.v2_gpu_s117_exp](https://nlp.johnsnowlabs.com/2022/09/25/asr_exp_w2v2t_pretraining_s117_gpu_fa.html) | [asr_exp_w2v2t_pretraining_s117_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_exp_w2v2t_pretraining_s117_gpu_fa.html) | Wav2Vec2ForCTC |
| fa | [fa.speech2text.wav2vec_xlsr.v2_s44_exp](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xls_r_s44_fa.html) | [asr_exp_w2v2t_xls_r_s44](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xls_r_s44_fa.html) | Wav2Vec2ForCTC |
| fi | [fi.speech2text.wav2vec2.voxpopuli.v2_base](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_base_10k_voxpopuli_fi.html) | [asr_wav2vec2_base_10k_voxpopuli](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_base_10k_voxpopuli_fi.html) | Wav2Vec2ForCTC |
| fi | [fi.speech2text.wav2vec_xlsrby_aapot](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_xlsr_1b_finnish_lm_by_aapot_fi.html) | [asr_wav2vec2_xlsr_1b_finnish_lm_by_aapot](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_xlsr_1b_finnish_lm_by_aapot_fi.html) | Wav2Vec2ForCTC |
| fon | [fon.speech2text.wav2vec_xlsr](https://nlp.johnsnowlabs.com/2022/09/24/asr_fonxlsr_fon.html) | [asr_fonxlsr](https://nlp.johnsnowlabs.com/2022/09/24/asr_fonxlsr_fon.html) | Wav2Vec2ForCTC |
| fr | [fr.speech2text.wav2vec_xlsr.v2_s800_exp](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xlsr_53_s800_fr.html) | [asr_exp_w2v2t_xlsr_53_s800](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xlsr_53_s800_fr.html) | Wav2Vec2ForCTC |
| gu | [gu.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_gpu_gu.html) | [asr_wav2vec2_large_xlsr_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_gpu_gu.html) | Wav2Vec2ForCTC |
| hi | [hi.speech2text.wav2vec2.by_harveenchadha](https://nlp.johnsnowlabs.com/2022/09/26/asr_hindi_model_with_lm_vakyansh_hi.html) | [asr_hindi_model_with_lm_vakyansh](https://nlp.johnsnowlabs.com/2022/09/26/asr_hindi_model_with_lm_vakyansh_hi.html) | Wav2Vec2ForCTC |
| hi | [hi.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_hindi_gpu_hi.html) | [asr_wav2vec2_large_xlsr_hindi_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_hindi_gpu_hi.html) | Wav2Vec2ForCTC |
| hu | [hu.speech2text.wav2vec2.voxpopuli.v2_base_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_base_10k_voxpopuli_gpu_hu.html) | [asr_wav2vec2_base_10k_voxpopuli_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_base_10k_voxpopuli_gpu_hu.html) | Wav2Vec2ForCTC |
| hu | [hu.speech2text.wav2vec_xlsr.v2_large_gpu.by_gchhablani](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_gpu_hu.html) | [asr_wav2vec2_large_xlsr_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_gpu_hu.html) | Wav2Vec2ForCTC |
| id | [id.speech2text.wav2vec_xlsr.v2_s449_exp](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xlsr_53_s449_id.html) | [asr_exp_w2v2t_xlsr_53_s449](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xlsr_53_s449_id.html) | Wav2Vec2ForCTC |
| it | [it.speech2text.wav2vec2.v2_gpu_s149_vp_exp](https://nlp.johnsnowlabs.com/2022/09/25/asr_exp_w2v2t_vp_100k_s149_gpu_it.html) | [asr_exp_w2v2t_vp_100k_s149_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_exp_w2v2t_vp_100k_s149_gpu_it.html) | Wav2Vec2ForCTC |
| it | [it.speech2text.wav2vec_xlsr.v2_s417_exp](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xls_r_s417_it.html) | [asr_exp_w2v2t_xls_r_s417](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xls_r_s417_it.html) | Wav2Vec2ForCTC |
| ja | [ja.speech2text.wav2vec_xlsr.v2_large](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_japanese_hiragana_ja.html) | [asr_wav2vec2_large_xlsr_japanese_hiragana](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_japanese_hiragana_ja.html) | Wav2Vec2ForCTC |
| ko | [ko.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_korean_gpu_ko.html) | [asr_wav2vec2_large_xlsr_korean_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_korean_gpu_ko.html) | Wav2Vec2ForCTC |
| kr | [kr.speech2text.wav2vec_xlsr.v2](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_xlsr_korean_senior_kr.html) | [asr_wav2vec2_xlsr_korean_senior](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_xlsr_korean_senior_kr.html) | Wav2Vec2ForCTC |
| kr | [kr.speech2text.wav2vec_xlsr.v2_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_xlsr_korean_senior_gpu_kr.html) | [asr_wav2vec2_xlsr_korean_senior_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_xlsr_korean_senior_gpu_kr.html) | Wav2Vec2ForCTC |
| ku | [ku.speech2text.wav2vec_xlsr.gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_xlsr_kurmanji_kurdish_gpu_ku.html) | [asr_xlsr_kurmanji_kurdish_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_xlsr_kurmanji_kurdish_gpu_ku.html) | Wav2Vec2ForCTC |
| ky | [ky.speech2text.wav2vec_xlsr.v2_large](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_kyrgyz_ky.html) | [asr_wav2vec2_large_xlsr_53_kyrgyz](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_kyrgyz_ky.html) | Wav2Vec2ForCTC |
| ky | [ky.speech2text.wav2vec_xlsr.v2_large_gpu.by_iarfmoose](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_kyrgyz_by_iarfmoose_gpu_ky.html) | [asr_wav2vec2_large_xlsr_kyrgyz_by_iarfmoose_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_kyrgyz_by_iarfmoose_gpu_ky.html) | Wav2Vec2ForCTC |
| la | [la.speech2text.wav2vec2.v2_base](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_base_latin_la.html) | [asr_wav2vec2_base_latin](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_base_latin_la.html) | Wav2Vec2ForCTC |
| la | [la.speech2text.wav2vec2.v2_base_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_base_latin_gpu_la.html) | [asr_wav2vec2_base_latin_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_base_latin_gpu_la.html) | Wav2Vec2ForCTC |
| lg | [lg.speech2text.wav2vec_xlsr.v2_multilingual_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_xlsr_multilingual_56_gpu_lg.html) | [asr_wav2vec2_xlsr_multilingual_56_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_xlsr_multilingual_56_gpu_lg.html) | Wav2Vec2ForCTC |
| lt | [lt.speech2text.wav2vec_xlsr.v2_large_gpu.by_dundar](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_53_lithuanian_by_dundar_gpu_lt.html) | [asr_wav2vec2_large_xlsr_53_lithuanian_by_dundar_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_53_lithuanian_by_dundar_gpu_lt.html) | Wav2Vec2ForCTC |
| lv | [lv.speech2text.wav2vec_xlsr.v2_large](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_latvian_lv.html) | [asr_wav2vec2_large_xlsr_53_latvian](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_latvian_lv.html) | Wav2Vec2ForCTC |
| lv | [lv.speech2text.wav2vec_xlsr.v2_large_gpu.by_jimregan](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_latvian_gpu_lv.html) | [asr_wav2vec2_large_xlsr_latvian_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_latvian_gpu_lv.html) | Wav2Vec2ForCTC |
| mn | [mn.speech2text.wav2vec_xlsr.v2_large_gpu.by_manandey](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_mongolian_by_manandey_gpu_mn.html) | [asr_wav2vec2_large_xlsr_mongolian_by_manandey_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_mongolian_by_manandey_gpu_mn.html) | Wav2Vec2ForCTC |
| nl | [nl.speech2text.wav2vec_xlsr.v2_s972_exp](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xlsr_53_s972_nl.html) | [asr_exp_w2v2t_xlsr_53_s972](https://nlp.johnsnowlabs.com/2022/09/26/asr_exp_w2v2t_xlsr_53_s972_nl.html) | Wav2Vec2ForCTC |
| pt | [pt.speech2text.wav2vec_xlsr.voxforge1.gpu.by_lgris](https://nlp.johnsnowlabs.com/2022/09/24/asr_bp_voxforge1_xlsr_gpu_pt.html) | [asr_bp_voxforge1_xlsr_gpu](https://nlp.johnsnowlabs.com/2022/09/24/asr_bp_voxforge1_xlsr_gpu_pt.html) | Wav2Vec2ForCTC |
| ro | [ro.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_romanian_by_gmihaila_gpu_ro.html) | [asr_wav2vec2_large_xlsr_53_romanian_by_gmihaila_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_romanian_by_gmihaila_gpu_ro.html) | Wav2Vec2ForCTC |
| sg | [sg.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_swiss_german_gpu_sg.html) | [asr_wav2vec2_large_xlsr_53_swiss_german_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_swiss_german_gpu_sg.html) | Wav2Vec2ForCTC |
| su | [su.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_sundanese_gpu_su.html) | [asr_wav2vec2_large_xlsr_sundanese_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_sundanese_gpu_su.html) | Wav2Vec2ForCTC |
| sv | [sv.speech2text.wav2vec_xlsr.v2_large_gpu.by_marma](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_swedish_gpu_sv.html) | [asr_wav2vec2_large_xlsr_swedish_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_swedish_gpu_sv.html) | Wav2Vec2ForCTC |
| tt | [tt.speech2text.wav2vec_xlsr.v2_large_small](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_W2V2_TATAR_SMALL_tt.html) | [asr_wav2vec2_large_xlsr_53_W2V2_TATAR_SMALL](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_53_W2V2_TATAR_SMALL_tt.html) | Wav2Vec2ForCTC |
| tw | [tw.speech2text.wav2vec_xlsr.v2](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2large_xlsr_akan_tw.html) | [asr_wav2vec2large_xlsr_akan](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2large_xlsr_akan_tw.html) | Wav2Vec2ForCTC |
| uz | [uz.speech2text.wav2vec2](https://nlp.johnsnowlabs.com/2022/09/26/asr_uzbek_stt_uz.html) | [asr_uzbek_stt](https://nlp.johnsnowlabs.com/2022/09/26/asr_uzbek_stt_uz.html) | Wav2Vec2ForCTC |
| vi | [vi.speech2text.wav2vec_xlsr.v2_large_gpu.by_not_tanh](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_53_vietnamese_by_not_tanh_gpu_vi.html) | [asr_wav2vec2_large_xlsr_53_vietnamese_by_not_tanh_gpu](https://nlp.johnsnowlabs.com/2022/09/25/asr_wav2vec2_large_xlsr_53_vietnamese_by_not_tanh_gpu_vi.html) | Wav2Vec2ForCTC |
| wo | [wo.speech2text.wav2vec_xlsr.v2_300m_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_av2vec2_xls_r_300m_wolof_lm_gpu_wo.html) | [asr_av2vec2_xls_r_300m_wolof_lm_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_av2vec2_xls_r_300m_wolof_lm_gpu_wo.html) | Wav2Vec2ForCTC |
| yue | [yue.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu_yue.html) | [asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu_yue.html) | Wav2Vec2ForCTC |



Image Classification Models Overview


| Language | NLU Reference | Spark NLP Reference | Annotator Class |
|:---------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------|
| en | [en.classify_image.Check_GoodBad_Teeth](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Check_GoodBad_Teeth_en_3_0.html) | [image_classifier_vit_Check_GoodBad_Teeth](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Check_GoodBad_Teeth_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.Check_Gum_Teeth](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Check_Gum_Teeth_en_3_0.html) | [image_classifier_vit_Check_Gum_Teeth](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Check_Gum_Teeth_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.Check_Missing_Teeth](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Check_Missing_Teeth_en_3_0.html) | [image_classifier_vit_Check_Missing_Teeth](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Check_Missing_Teeth_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.Infrastructures](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Infrastructures_en_3_0.html) | [image_classifier_vit_Infrastructures](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Infrastructures_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.Insectodoptera](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Insectodoptera_en_3_0.html) | [image_classifier_vit_Insectodoptera](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Insectodoptera_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.Tomato_Leaf_Classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Tomato_Leaf_Classifier_en_3_0.html) | [image_classifier_vit_Tomato_Leaf_Classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Tomato_Leaf_Classifier_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.Visual_transformer_chihuahua_cookies](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Visual_transformer_chihuahua_cookies_en_3_0.html) | [image_classifier_vit_Visual_transformer_chihuahua_cookies](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_Visual_transformer_chihuahua_cookies_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image._spectrogram](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit__spectrogram_en_3_0.html) | [image_classifier_vit__spectrogram](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit__spectrogram_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.age_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_age_classifier_en_3_0.html) | [image_classifier_vit_age_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_age_classifier_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.airplanes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_airplanes_en_3_0.html) | [image_classifier_vit_airplanes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_airplanes_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.animal_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_animal_classifier_en_3_0.html) | [image_classifier_vit_animal_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_animal_classifier_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.anomaly](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_anomaly_en_3_0.html) | [image_classifier_vit_anomaly](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_anomaly_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.apes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_apes_en_3_0.html) | [image_classifier_vit_apes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_apes_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.autotrain_cifar10__base](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_autotrain_cifar10__base_en_3_0.html) | [image_classifier_vit_autotrain_cifar10__base](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_autotrain_cifar10__base_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.autotrain_dog_vs_food](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_autotrain_dog_vs_food_en_3_0.html) | [image_classifier_vit_autotrain_dog_vs_food](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_autotrain_dog_vs_food_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.baked_goods](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_baked_goods_en_3_0.html) | [image_classifier_vit_baked_goods](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_baked_goods_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_beans](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_beans_en_3_0.html) | [image_classifier_vit_base_beans](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_beans_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_cats_vs_dogs](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_cats_vs_dogs_en_3_0.html) | [image_classifier_vit_base_cats_vs_dogs](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_cats_vs_dogs_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_cifar10](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_cifar10_en_3_0.html) | [image_classifier_vit_base_cifar10](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_cifar10_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_food101](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_food101_en_3_0.html) | [image_classifier_vit_base_food101](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_food101_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_movie_scenes_v1](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_movie_scenes_v1_en_3_0.html) | [image_classifier_vit_base_movie_scenes_v1](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_movie_scenes_v1_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_mri](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_mri_en_3_0.html) | [image_classifier_vit_base_mri](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_mri_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_en_3_0.html) | [image_classifier_vit_base_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224.by_google](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_en_3_0.html) | [image_classifier_vit_base_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224_cifar10](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_cifar10_en_3_0.html) | [image_classifier_vit_base_patch16_224_cifar10](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_cifar10_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224_finetuned_eurosat](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_finetuned_eurosat_en_3_0.html) | [image_classifier_vit_base_patch16_224_finetuned_eurosat](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_finetuned_eurosat_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224_finetuned_kvasirv2_colonoscopy](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy_en_3_0.html) | [image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224_in21k_snacks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_in21k_snacks_en_3_0.html) | [image_classifier_vit_base_patch16_224_in21k_snacks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_in21k_snacks_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224_in21k_ucSat](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_in21k_ucSat_en_3_0.html) | [image_classifier_vit_base_patch16_224_in21k_ucSat](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_in21k_ucSat_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_224_recylce_ft](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_recylce_ft_en_3_0.html) | [image_classifier_vit_base_patch16_224_recylce_ft](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_224_recylce_ft_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_384](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_384_en_3_0.html) | [image_classifier_vit_base_patch16_384](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_384_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch16_384.by_google](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_384_en_3_0.html) | [image_classifier_vit_base_patch16_384](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch16_384_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_patch32_384.by_google](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch32_384_en_3_0.html) | [image_classifier_vit_base_patch32_384](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_patch32_384_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.base_xray_pneumonia](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_xray_pneumonia_en_3_0.html) | [image_classifier_vit_base_xray_pneumonia](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_base_xray_pneumonia_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.baseball_stadium_foods](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_baseball_stadium_foods_en_3_0.html) | [image_classifier_vit_baseball_stadium_foods](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_baseball_stadium_foods_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.beer_vs_wine](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_beer_vs_wine_en_3_0.html) | [image_classifier_vit_beer_vs_wine](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_beer_vs_wine_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.beer_whisky_wine_detection](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_beer_whisky_wine_detection_en_3_0.html) | [image_classifier_vit_beer_whisky_wine_detection](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_beer_whisky_wine_detection_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.blocks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_blocks_en_3_0.html) | [image_classifier_vit_blocks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_blocks_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.cifar10](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_cifar10_en_3_0.html) | [image_classifier_vit_cifar10](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_cifar10_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.cifar_10_2](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_cifar_10_2_en_3_0.html) | [image_classifier_vit_cifar_10_2](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_cifar_10_2_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.computer_stuff](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_computer_stuff_en_3_0.html) | [image_classifier_vit_computer_stuff](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_computer_stuff_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.croupier_creature_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_croupier_creature_classifier_en_3_0.html) | [image_classifier_vit_croupier_creature_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_croupier_creature_classifier_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_base_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_base_patch16_224_en_3_0.html) | [image_classifier_vit_deit_base_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_base_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_base_patch16_224.by_facebook](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_base_patch16_224_en_3_0.html) | [image_classifier_vit_deit_base_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_base_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_flyswot](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_flyswot_en_3_0.html) | [image_classifier_vit_deit_flyswot](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_flyswot_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_small_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_small_patch16_224_en_3_0.html) | [image_classifier_vit_deit_small_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_small_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_small_patch16_224.by_facebook](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_small_patch16_224_en_3_0.html) | [image_classifier_vit_deit_small_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_small_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_tiny_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_tiny_patch16_224_en_3_0.html) | [image_classifier_vit_deit_tiny_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_tiny_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.deit_tiny_patch16_224.by_facebook](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_tiny_patch16_224_en_3_0.html) | [image_classifier_vit_deit_tiny_patch16_224](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_deit_tiny_patch16_224_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.demo](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_demo_en_3_0.html) | [image_classifier_vit_demo](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_demo_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.denver_nyc_paris](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_denver_nyc_paris_en_3_0.html) | [image_classifier_vit_denver_nyc_paris](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_denver_nyc_paris_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.diam](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_diam_en_3_0.html) | [image_classifier_vit_diam](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_diam_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.digital](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_digital_en_3_0.html) | [image_classifier_vit_digital](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_digital_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dog](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_en_3_0.html) | [image_classifier_vit_dog](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dog_breed_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_breed_classifier_en_3_0.html) | [image_classifier_vit_dog_breed_classifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_breed_classifier_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dog_food__base_patch16_224_in21k](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_food__base_patch16_224_in21k_en_3_0.html) | [image_classifier_vit_dog_food__base_patch16_224_in21k](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_food__base_patch16_224_in21k_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dog_races](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_races_en_3_0.html) | [image_classifier_vit_dog_races](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_races_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dog_vs_chicken](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_vs_chicken_en_3_0.html) | [image_classifier_vit_dog_vs_chicken](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dog_vs_chicken_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.doggos_lol](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_doggos_lol_en_3_0.html) | [image_classifier_vit_doggos_lol](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_doggos_lol_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dogs](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dogs_en_3_0.html) | [image_classifier_vit_dogs](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dogs_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.dwarf_goats](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dwarf_goats_en_3_0.html) | [image_classifier_vit_dwarf_goats](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_dwarf_goats_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.electric_2](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_electric_2_en_3_0.html) | [image_classifier_vit_electric_2](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_electric_2_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.electric_pole_type_classification](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_electric_pole_type_classification_en_3_0.html) | [image_classifier_vit_electric_pole_type_classification](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_electric_pole_type_classification_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.ex_for_evan](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_ex_for_evan_en_3_0.html) | [image_classifier_vit_ex_for_evan](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_ex_for_evan_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.finetuned_eurosat_kornia](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_finetuned_eurosat_kornia_en_3_0.html) | [image_classifier_vit_finetuned_eurosat_kornia](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_finetuned_eurosat_kornia_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.flowers](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_flowers_en_3_0.html) | [image_classifier_vit_flowers](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_flowers_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.food](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_food_en_3_0.html) | [image_classifier_vit_food](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_food_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.fruits](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_fruits_en_3_0.html) | [image_classifier_vit_fruits](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_fruits_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.garbage_classification](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_garbage_classification_en_3_0.html) | [image_classifier_vit_garbage_classification](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_garbage_classification_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.grain](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_grain_en_3_0.html) | [image_classifier_vit_grain](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_grain_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.greens](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_greens_en_3_0.html) | [image_classifier_vit_greens](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_greens_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.hot_dog_or_sandwich](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_hot_dog_or_sandwich_en_3_0.html) | [image_classifier_vit_hot_dog_or_sandwich](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_hot_dog_or_sandwich_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.hotdog_not_hotdog](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_hotdog_not_hotdog_en_3_0.html) | [image_classifier_vit_hotdog_not_hotdog](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_hotdog_not_hotdog_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.housing_categories](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_housing_categories_en_3_0.html) | [image_classifier_vit_housing_categories](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_housing_categories_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.hugging_geese](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_hugging_geese_en_3_0.html) | [image_classifier_vit_hugging_geese](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_hugging_geese_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.ice_cream](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_ice_cream_en_3_0.html) | [image_classifier_vit_ice_cream](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_ice_cream_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.iiif_manuscript_](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_iiif_manuscript__en_3_0.html) | [image_classifier_vit_iiif_manuscript_](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_iiif_manuscript__en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.indian_snacks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_indian_snacks_en_3_0.html) | [image_classifier_vit_indian_snacks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_indian_snacks_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.koala_panda_wombat](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_koala_panda_wombat_en_3_0.html) | [image_classifier_vit_koala_panda_wombat](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_koala_panda_wombat_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.lawn_weeds](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lawn_weeds_en_3_0.html) | [image_classifier_vit_lawn_weeds](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lawn_weeds_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.llama_alpaca_guanaco_vicuna](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_alpaca_guanaco_vicuna_en_3_0.html) | [image_classifier_vit_llama_alpaca_guanaco_vicuna](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_alpaca_guanaco_vicuna_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.llama_alpaca_snake](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_alpaca_snake_en_3_0.html) | [image_classifier_vit_llama_alpaca_snake](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_alpaca_snake_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.llama_or_potato](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_or_potato_en_3_0.html) | [image_classifier_vit_llama_or_potato](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_or_potato_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.llama_or_what](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_or_what_en_3_0.html) | [image_classifier_vit_llama_or_what](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_llama_or_what_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.lotr](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lotr_en_3_0.html) | [image_classifier_vit_lotr](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lotr_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.lucky_model](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lucky_model_en_3_0.html) | [image_classifier_vit_lucky_model](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lucky_model_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.lung_cancer](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lung_cancer_en_3_0.html) | [image_classifier_vit_lung_cancer](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_lung_cancer_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.mit_indoor_scenes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_mit_indoor_scenes_en_3_0.html) | [image_classifier_vit_mit_indoor_scenes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_mit_indoor_scenes_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.modelversion01](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_modelversion01_en_3_0.html) | [image_classifier_vit_modelversion01](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_modelversion01_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.my_bean_VIT](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_my_bean_VIT_en_3_0.html) | [image_classifier_vit_my_bean_VIT](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_my_bean_VIT_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.new_york_tokyo_london](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_new_york_tokyo_london_en_3_0.html) | [image_classifier_vit_new_york_tokyo_london](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_new_york_tokyo_london_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.occupation_prediction](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_occupation_prediction_en_3_0.html) | [image_classifier_vit_occupation_prediction](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_occupation_prediction_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.opencampus_age_detection](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_opencampus_age_detection_en_3_0.html) | [image_classifier_vit_opencampus_age_detection](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_opencampus_age_detection_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.orcs_and_friends](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_orcs_and_friends_en_3_0.html) | [image_classifier_vit_orcs_and_friends](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_orcs_and_friends_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.oz_fauna](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_oz_fauna_en_3_0.html) | [image_classifier_vit_oz_fauna](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_oz_fauna_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.pasta_pizza_ravioli](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_pasta_pizza_ravioli_en_3_0.html) | [image_classifier_vit_pasta_pizza_ravioli](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_pasta_pizza_ravioli_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.pasta_shapes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_pasta_shapes_en_3_0.html) | [image_classifier_vit_pasta_shapes](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_pasta_shapes_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.places](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_places_en_3_0.html) | [image_classifier_vit_places](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_places_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.planes_airlines](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_planes_airlines_en_3_0.html) | [image_classifier_vit_planes_airlines](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_planes_airlines_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.planes_trains_automobiles](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_planes_trains_automobiles_en_3_0.html) | [image_classifier_vit_planes_trains_automobiles](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_planes_trains_automobiles_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.puppies_classify](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_puppies_classify_en_3_0.html) | [image_classifier_vit_puppies_classify](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_puppies_classify_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.rare_bottle](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_rare_bottle_en_3_0.html) | [image_classifier_vit_rare_bottle](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_rare_bottle_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.roomclassifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_roomclassifier_en_3_0.html) | [image_classifier_vit_roomclassifier](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_roomclassifier_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.rust_image_classification_1](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_rust_image_classification_1_en_3_0.html) | [image_classifier_vit_rust_image_classification_1](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_rust_image_classification_1_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.skin_type](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_skin_type_en_3_0.html) | [image_classifier_vit_skin_type](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_skin_type_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.snacks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_snacks_en_3_0.html) | [image_classifier_vit_snacks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_snacks_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.south_indian_foods](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_south_indian_foods_en_3_0.html) | [image_classifier_vit_south_indian_foods](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_south_indian_foods_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.string_instrument_detector](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_string_instrument_detector_en_3_0.html) | [image_classifier_vit_string_instrument_detector](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_string_instrument_detector_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.vc_bantai__withoutAMBI_adunest](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_vc_bantai__withoutAMBI_adunest_en_3_0.html) | [image_classifier_vit_vc_bantai__withoutAMBI_adunest](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_vc_bantai__withoutAMBI_adunest_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.trainer_rare_puppers](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_trainer_rare_puppers_en_3_0.html) | [image_classifier_vit_trainer_rare_puppers](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_trainer_rare_puppers_en_3_0.html) | ViTForImageClassification |
| en | [en.classify_image.world_landmarks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_world_landmarks_en_3_0.html) | [image_classifier_vit_world_landmarks](https://nlp.johnsnowlabs.com/2022/08/10/image_classifier_vit_world_landmarks_en_3_0.html) | ViTForImageClassification |




Install NLU

python
pip install nlu pyspark



Additional NLU resources
* [140+ NLU Tutorials](https://nlu.johnsnowlabs.com/docs/en/notebooks)
* [NLU in Action](https://nlp.johnsnowlabs.com/demo)
* [Streamlit visualizations docs](https://nlu.johnsnowlabs.com/docs/en/streamlit_viz_examples)
* The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models).
* [Spark NLP publications](https://medium.com/spark-nlp)
* [NLU documentation](https://nlu.johnsnowlabs.com/docs/en/install)
* [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU!

4.0

Can be found on the [NLU website](https://nlu.johnsnowlabs.com/docs/en/release_notes) because of Github Limitations



| NLU Reference | Spark NLP Reference | Task | Language Name(s) | Annotator Class |
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------|:-------------------------------------------------------------|:-------------------------------|
| [bn.answer_question.tydiqa.multi_lingual_bert](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_mbert_bengali_tydiqa_qa_bn_3_0.html) | [bert_qa_mbert_bengali_tydiqa_qa](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_mbert_bengali_tydiqa_qa_bn_3_0.html) | Question Answering | [Bengali](https://iso639-3.sil.org/code/ben) | BertForQuestionAnswering |
| [es.answer_question.squadv2.electra.small](https://nlp.johnsnowlabs.com/2022/06/22/electra_qa_biomedtra_small_es_squad2_es_3_0.html) | [electra_qa_biomedtra_small_es_squad2](https://nlp.johnsnowlabs.com/2022/06/22/electra_qa_biomedtra_small_es_squad2_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squad_sqac.bert.base_cased](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squadv2.bert.base_cased.by_MMG](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_MMG_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_MMG](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_MMG_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squadv2.bert.base_cased.by_mrm8488](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squadv2.bert.distilled_base_cased](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_distill_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488_es_3_0.html) | [bert_qa_distill_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_distill_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squad.ruperta.base.by_mrm8488](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_RuPERTa_base_finetuned_squadv1_es_3_0.html) | [roberta_qa_RuPERTa_base_finetuned_squadv1](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_RuPERTa_base_finetuned_squadv1_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squadv2.roberta.base](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_bne_squad2_hackathon_pln_es_3_0.html) | [roberta_qa_roberta_base_bne_squad2_hackathon_pln](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_bne_squad2_hackathon_pln_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squadv2_sqac.bert.base_cased_spa.by_MMG](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_finetuned_sqac_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_finetuned_sqac](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_finetuned_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squadv2_bio_medical.roberta.base](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_biomedical_es_squad2_hackathon_pln_es_3_0.html) | [roberta_qa_roberta_base_biomedical_es_squad2_hackathon_pln](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_biomedical_es_squad2_hackathon_pln_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squadv2_clinical_bio_medical.roberta.base](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_biomedical_clinical_es_squad2_hackathon_pln_es_3_0.html) | [roberta_qa_roberta_base_biomedical_clinical_es_squad2_hackathon_pln](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_biomedical_clinical_es_squad2_hackathon_pln_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squadv2_sqac.bert.base_cased.by_MMG](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad2_es_MMG_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad2_es_MMG](https://nlp.johnsnowlabs.com/2022/06/03/bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad2_es_MMG_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squadv2_sqac.bert.base_cased_v2.by_MMG](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_finetuned_sqac_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_finetuned_sqac](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_finetuned_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.xlm_roberta.base](https://nlp.johnsnowlabs.com/2022/06/23/xlm_roberta_qa_xlm_roberta_base_spanish_es_3_0.html) | [xlm_roberta_qa_xlm_roberta_base_spanish](https://nlp.johnsnowlabs.com/2022/06/23/xlm_roberta_qa_xlm_roberta_base_spanish_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | XlmRoBertaForQuestionAnswering |
| [es.answer_question.xlm_roberta.multilingual_large](https://nlp.johnsnowlabs.com/2022/06/24/xlm_roberta_qa_xlm_roberta_large_qa_multilingual_finedtuned_ru_ru_AlexKay_es_3_0.html) | [xlm_roberta_qa_xlm_roberta_large_qa_multilingual_finedtuned_ru_ru_AlexKay](https://nlp.johnsnowlabs.com/2022/06/24/xlm_roberta_qa_xlm_roberta_large_qa_multilingual_finedtuned_ru_ru_AlexKay_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | XlmRoBertaForQuestionAnswering |
| [es.answer_question.squad.roberta.large.by_stevemobs](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_large_fine_tuned_squad_es_stevemobs_es_3_0.html) | [roberta_qa_roberta_large_fine_tuned_squad_es_stevemobs](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_large_fine_tuned_squad_es_stevemobs_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squadv2.roberta.base_v2](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_RuPERTa_base_finetuned_squadv2_es_3_0.html) | [roberta_qa_RuPERTa_base_finetuned_squadv2](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_RuPERTa_base_finetuned_squadv2_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squad.roberta.large.by_jamarju](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_large_bne_squad_2.0_es_jamarju_es_3_0.html) | [roberta_qa_roberta_large_bne_squad_2.0_es_jamarju](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_large_bne_squad_2.0_es_jamarju_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.roberta.large.by_BSC-TeMU](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_BSC_TeMU_roberta_large_bne_sqac_es_3_0.html) | [roberta_qa_BSC_TeMU_roberta_large_bne_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_BSC_TeMU_roberta_large_bne_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squad.roberta.base.by_jamarju](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_bne_squad_2.0_es_jamarju_es_3_0.html) | [roberta_qa_roberta_base_bne_squad_2.0_es_jamarju](https://nlp.johnsnowlabs.com/2022/06/21/roberta_qa_roberta_base_bne_squad_2.0_es_jamarju_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squad.roberta.base_4096.by_mrm8488](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_longformer_base_4096_spanish_finetuned_squad_es_3_0.html) | [roberta_qa_longformer_base_4096_spanish_finetuned_squad](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_longformer_base_4096_spanish_finetuned_squad_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.distil_bert.base_uncased](https://nlp.johnsnowlabs.com/2022/06/08/distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_tar_es_3_0.html) | [distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_tar](https://nlp.johnsnowlabs.com/2022/06/08/distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_tar_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | DistilBertForQuestionAnswering |
| [es.answer_question.mlqa.distil_bert.base_uncased](https://nlp.johnsnowlabs.com/2022/06/08/distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_mlqa_es_3_0.html) | [distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_mlqa](https://nlp.johnsnowlabs.com/2022/06/08/distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_mlqa_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | DistilBertForQuestionAnswering |
| [es.answer_question.sqac.bert.base](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_beto_base_spanish_sqac_es_3_0.html) | [bert_qa_beto_base_spanish_sqac](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_beto_base_spanish_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.sqac.distil_bert.base_uncased](https://nlp.johnsnowlabs.com/2022/06/08/distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_sqac_es_3_0.html) | [distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_sqac](https://nlp.johnsnowlabs.com/2022/06/08/distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | DistilBertForQuestionAnswering |
| [es.answer_question.sqac.roberta.base.by_BSC-TeMU](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_BSC_TeMU_roberta_base_bne_sqac_es_3_0.html) | [roberta_qa_BSC_TeMU_roberta_base_bne_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_BSC_TeMU_roberta_base_bne_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.roberta.base.by_IIC](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_base_spanish_sqac_es_3_0.html) | [roberta_qa_roberta_base_spanish_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_base_spanish_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.bert.base_cased](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_es_3_0.html) | [bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.sqac.roberta.base.by_mrm8488](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es_3_0.html) | [roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.roberta.base.by_nlp-en-es](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_nlp_en_es_roberta_base_bne_finetuned_sqac_es_3_0.html) | [roberta_qa_nlp_en_es_roberta_base_bne_finetuned_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_nlp_en_es_roberta_base_bne_finetuned_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.roberta.large.by_PlanTL-GOB-ES](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_PlanTL_GOB_ES_roberta_large_bne_sqac_es_3_0.html) | [roberta_qa_PlanTL_GOB_ES_roberta_large_bne_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_PlanTL_GOB_ES_roberta_large_bne_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.roberta.large.by_nlp-en-es](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_bertin_large_finetuned_sqac_es_3_0.html) | [roberta_qa_bertin_large_finetuned_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_bertin_large_finetuned_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.squad.electra.small](https://nlp.johnsnowlabs.com/2022/06/22/electra_qa_electricidad_small_finetuned_squadv1_es_3_0.html) | [electra_qa_electricidad_small_finetuned_squadv1](https://nlp.johnsnowlabs.com/2022/06/22/electra_qa_electricidad_small_finetuned_squadv1_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | BertForQuestionAnswering |
| [es.answer_question.squad.roberta.base.by_IIC](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_base_spanish_squades_es_3_0.html) | [roberta_qa_roberta_base_spanish_squades](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_base_spanish_squades_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [es.answer_question.sqac.roberta.base.by_PlanTL-GOB-ES](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_PlanTL_GOB_ES_roberta_base_bne_sqac_es_3_0.html) | [roberta_qa_PlanTL_GOB_ES_roberta_base_bne_sqac](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_PlanTL_GOB_ES_roberta_base_bne_sqac_es_3_0.html) | Question Answering | [Castilian, Spanish](https://iso639-3.sil.org/code/spa) | RoBertaForQuestionAnswering |
| [ch.answer_question.xlm_roberta](https://nlp.johnsnowlabs.com/2022/06/23/xlm_roberta_qa_ADDI_CH_XLM_R_ch_3_0.html) | [xlm_roberta_qa_ADDI_CH_XLM_R](https://nlp.johnsnowlabs.com/2022/06/23/xlm_roberta_qa_ADDI_CH_XLM_R_ch_3_0.html) | Question Answering | [Chamorro](https://iso639-3.sil.org/code/cha) | XlmRoBertaForQuestionAnswering |
| [da.answer_question.squad.bert](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_danish_bert_botxo_qa_squad_da_3_0.html) | [bert_qa_danish_bert_botxo_qa_squad](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_danish_bert_botxo_qa_squad_da_3_0.html) | Question Answering | [Danish](https://iso639-3.sil.org/code/dan) | BertForQuestionAnswering |
| [da.answer_question.squad.xlmr_roberta.base](https://nlp.johnsnowlabs.com/2022/06/24/xlm_roberta_qa_xlmr_base_texas_squad_da_da_saattrupdan_da_3_0.html) | [xlm_roberta_qa_xlmr_base_texas_squad_da_da_saattrupdan](https://nlp.johnsnowlabs.com/2022/06/24/xlm_roberta_qa_xlmr_base_texas_squad_da_da_saattrupdan_da_3_0.html) | Question Answering | [Danish](https://iso639-3.sil.org/code/dan) | XlmRoBertaForQuestionAnswering |
| [nl.answer_question.squadv2.bert.multilingual_base_cased](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_multilingual_cased_finetuned_dutch_squad2_nl_3_0.html) | [bert_qa_bert_base_multilingual_cased_finetuned_dutch_squad2](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_bert_base_multilingual_cased_finetuned_dutch_squad2_nl_3_0.html) | Question Answering | [Dutch, Flemish](https://iso639-3.sil.org/code/nld) | BertForQuestionAnswering |
| [en.answer_question.squad.roberta.large.by_csarron](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_large_squad_v1_en_3_0.html) | [roberta_qa_roberta_large_squad_v1](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_large_squad_v1_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | RoBertaForQuestionAnswering |
| [en.answer_question.squad.roberta.large.by_rahulchakwate](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_large_finetuned_squad_en_3_0.html) | [roberta_qa_roberta_large_finetuned_squad](https://nlp.johnsnowlabs.com/2022/06/20/roberta_qa_roberta_large_finetuned_squad_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | RoBertaForQuestionAnswering |
| [en.answer_question.squad.scibert.by_amoux](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_scibert_nli_squad_en_3_0.html) | [bert_qa_scibert_nli_squad](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_scibert_nli_squad_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.scibert.by_ixa-ehu](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_SciBERT_SQuAD_QuAC_en_3_0.html) | [bert_qa_SciBERT_SQuAD_QuAC](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_SciBERT_SQuAD_QuAC_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.scibert.uncased](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_scibert_scivocab_uncased_squad_en_3_0.html) | [bert_qa_scibert_scivocab_uncased_squad](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_scibert_scivocab_uncased_squad_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_finetuned_squadv1_en_3_0.html) | [bert_qa_spanbert_finetuned_squadv1](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_finetuned_squadv1_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_1024d_seed_0](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_1024d_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_10_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_10_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_1024d_seed_2](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_2_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_2](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_2_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_1024d_seed_4](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_4_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_4](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_4_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_1024d_seed_8](https://nlp.johnsnowlabs.com/2022/06/06/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8](https://nlp.johnsnowlabs.com/2022/06/06/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_1024d_seed_6](https://nlp.johnsnowlabs.com/2022/06/06/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6](https://nlp.johnsnowlabs.com/2022/06/06/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_128d_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_128d_seed_4](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_128d_seed_6](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_128d_seed_8](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_256d_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_32d_seed_0](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_32d_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en_3_0.html) | [bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10](https://nlp.johnsnowlabs.com/2022/06/02/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en_3_0.html) | Question Answering | [English](https://iso639-3.sil.org/code/eng) | BertForQuestionAnswering |
| [en.answer_question.squad.span_bert.base_cased_32d_seed_2](https://nlp.joh

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