Sentence Similarity
Transformers
PyTorch
bert
feature-extraction
custom_code
text-embeddings-inference
Instructions to use efederici/multilingual-e5-small-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/multilingual-e5-small-4096 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("efederici/multilingual-e5-small-4096", trust_remote_code=True) model = AutoModel.from_pretrained("efederici/multilingual-e5-small-4096", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from efederici/multilingual-e5-small-4096: direct link, hf CLI and curl.
- Browser
- Download file 478 MB
-
https://huggingface.co/efederici/multilingual-e5-small-4096/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://efederici/multilingual-e5-small-4096/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/efederici/multilingual-e5-small-4096/resolve/main/pytorch_model.bin
478 MB
- Xet hash:
- 5641bdd1688eeded01ffd5c25cc935a632ddcca99a43bee26d13ac58231a5d3f
- Size of remote file:
- 478 MB
- SHA256:
- 54a9213044d4d1b74b0feae5ce8dd4d33d55b8b4cd61f34a1016ff1cf991ef8e
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