sentence-transformers
https://github.com/ukplab/sentence-transformers
Python
Sentence Embeddings with BERT & XLNet
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- Issues
- Text2Topic : a new loss function ?
- Why memory increases during training
- State-of-the-art pretrained model for sentence similarity/clustering?
- Allow extraction of revision id from model
- RuntimeError: Unable to find data type for weight_name='/encoder/layer.0/attention/output/dense/MatMul_output_0'. shape_inference failed to return a type probably this node is from a different domain or using an input produced by such an operator. This may happen if you quantize a model already quantized. You may use extra_options `DefaultTensorType` to indicate the default weight type, usually `onnx.TensorProto.FLOAT`.
- Can longer sequences be encoded? Are the encodings good?
- What is the maximum number of sentences that a fast cluster can cluster?
- Last Token Embedding not matching
- TypeError: T5EncoderModel.forward() got an unexpected keyword argument 'token_type_ids'
- Implementing Embedding Quantization for Dynamic Serving Contexts
- Docs
- Python not yet supported