Sentence Similarity
sentence-transformers
PyTorch
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use ef-zulla/e5-multi-sml-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ef-zulla/e5-multi-sml-torch with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ef-zulla/e5-multi-sml-torch") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ef-zulla/e5-multi-sml-torch: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/ef-zulla/e5-multi-sml-torch/resolve/main/tokenizer.json
- Command line
-
hf download hf://ef-zulla/e5-multi-sml-torch/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ef-zulla/e5-multi-sml-torch/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 4a54e04ca9acc0c713fba28dda620806eb4287667ab4606a538580d035406ab9
- Size of remote file:
- 17.1 MB
- SHA256:
- 2b3f6fc9286922cf30646a1957c81e5655f977d2204c9631b7624f21d6c641b5
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