Dicee

We're happy to announce the 0.0.7 release.

You can install it with `pip install dicee==0.0.7`

We're happy to announce the 0.0.6 release.

You can install it with `pip install dicee==0.0.6`


Major updates

1. Model Parallelism via PyTorch Lightning

2. Model Paralelisim via prediction averarning is tested.

3. AllvsAll training is implemented and regression tests are added


Todos for the next release

1. Multi-hop Query Answering
2. **8bit Training**:

We're happy to announce the 0.0.5 release.

You can install it with `pip install dicee==0.0.5`


Major updates

1. Pykeen models can be trained without out-of-memory caused by using reguralizers wo collect_regularization_term (see 1297) .

2. Via `--sparql_endpoint` argument, KGE models can be trained on triples stored in a triple store.

3. Via `rdflib`, many different formatted KGs can be read into memory.

4. We added more tests and documented our code.


Todos for the next release

1. **Model Parallelism**:
2. **8bit Training**:

We're happy to announce the 1.0.4 release.

You can install it with `pip install dicee`


Major updates

The knowledge graph embedding models implemented in Pykeen can be used within our framework.
Hence, [the distributed training column of the Table 1 in PyKEEN paper](https://arxiv.org/pdf/2007.14175.pdf) can be checked via our framework 🎉.

We're happy to announce the 1.0.3 release.

You can install it with `pip install dicee`


Major updates

Distributed Data Parallel training in a multi-node setting is available.

We're happy to announce the 1.0.2 release.

You can install it with `pip install dicee`