Download pre-trained sentence-transformers model locally

Question

I am using the SentenceTransformers library (here: https://pypi.org/project/sentence-transformers/#pretrained-models) for creating embeddings of sentences using the pre-trained model bert-base-nli-mean-tokens. I have an application that will be deployed to a device that does not have internet access. Here, it's already been answered, how to save the model Download pre-trained BERT model locally. Yet I'm stuck at loading the saved model from the locally saved path.

When I try to save the model using the above-mentioned technique, these are the output files:

('/bert-base-nli-mean-tokens/tokenizer_config.json',
 '/bert-base-nli-mean-tokens/special_tokens_map.json',
 '/bert-base-nli-mean-tokens/vocab.txt',
 '/bert-base-nli-mean-tokens/added_tokens.json')

When I try to load it in the memory, using

tokenizer = AutoTokenizer.from_pretrained(to_save_path)

I'm getting

Can't load config for '/bert-base-nli-mean-tokens'. Make sure that:

- '/bert-base-nli-mean-tokens' is a correct model identifier listed on 'https://huggingface.co/models'

- or '/bert-base-nli-mean-tokens' is the correct path to a directory containing a config.json 

Answer 1

You can download and load the model like this

from sentence_transformers import SentenceTransformer
modelPath = "local/path/to/model

model = SentenceTransformer('bert-base-nli-stsb-mean-tokens')
model.save(modelPath)
model = SentenceTransformer(modelPath)

this worked for me.You can check the SBERT documentation for model details for the SentenceTransformer class [Here][1]

[1]: https://www.sbert.net/docs/package_reference/SentenceTransformer.html#:~:text=class,Optional%5Bstr%5D%20%3D%20None)