Getting specific models, e.g. InferSent model

[githubrandomuser2017]

I see on your documentation page that there are a variety of models we can use, e.g. roberta-large-nli-stsb-mean-tokens.

How are these model names related to the model files found under sentence_transformers/models/? I see files like BERT.py, T5.py, and LSTM.py.

I'm just looking to see if you have a pretrained model that uses the InferSent encoder (LSTM max pooling).

[nreimers]

The python files in sentence_transformers/models are building block to create sentence embedding models. For an InferSent Style model, you would need an LSTM layer followed by a Pooling layer with max_pooling.

For an example, see: https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/avg_word_embeddings/training_stsbenchmark_bilstm.py

These models need to be tuned on suitable data to produce meaningful sentence embeddings.

The pre-trained model page lists different pre-trained models. These models were trained on different datasets and produce meaningful sentence embeddings. They can be used without the need of any training.

Best Nils Reimers

[githubrandomuser2017]

Thank you.