sentence-transformers
https://github.com/ukplab/sentence-transformers
Python
Sentence Embeddings with BERT & XLNet
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- Issues
- reducing `encode_multi_process` GPU memory usage
- Giving hard_negative a higher weight when calculating loss
- how to keep `encode_multi_process` output on the GPU
- MultipleNegativesSymmetricRankingLoss (potential optimization opportunity)
- Sentence Transformers / datasets dependency.
- Dask vs multiprocessing
- Inference speed difference when using sentence-transformers (python) and candle (rust)
- Cross Encoders do not free GPU memory after execution
- encode Function Returns NaN Embeddings for Some Tokens When Called on All Vocabulary
- [`fix`] Quantization of token embeddings
- Docs
- Python not yet supported