Languagemodels

Changed

- Remove explicit setuptools dependency (see [CTranslate21526](https://github.com/OpenNMT/CTranslate2/pull/1526))

Fixed

- Reduce model size when not using a CPU in Colab

Changed

- Default to 8GB model size on Colab
- Allow 2048 token response by default on Colab
- Use Colab GPU by default if available
- Skip returning prompt for decoder-only models
- Ensure whitespace is removed from decoder-only outputs

Added

- Add neural-chat-7b-v3-1 as default 8GB model
- Add max_tokens config option

Added

- Add gte-tiny embedding model
- Properly support Python 3.12

Fixed

- Removed extra classification prompt when performing classification with generative models
- Prevent doubling of special tokens during classification

Changed

- Use per-model instruction formats
- Batch chunk embeddings for faster performance embedding larger documents

Added

- Automatically use query prefixes as needed for embeddings
- Add phi-1.5 model
- Add dialogstudio base model
- Add support for gte-small embeddings
- Add support for bge-small-en embeddings

Fixed

- Allow token suppression on decoder-only models
- Remove HTML comments appearing in some wiki pages

Changed

- Model names no longer include backend and quantization info
- Default to CPU inference unless GPU enabled using `lm.config["device"]="auto"`

Added

- Add quantization info to config and use it for memory usage calculation

Fixed

- Increase repetition penalty to 1.3 from 1.2 to help avoid repetition in smaller models

Changed

- Improve semantic meaning of chunk heading
- Remove sentencepiece dependency

Added

- Support GPT-based models
- Add `code` generation function
- Create new configuration system
- Use CUDA if available

Fixed

- Use non-greedy sampling on `complete` function
- Decrease chance of splitting chunks on decimal points
- Correct assistant example