Feature Extraction
sentence-transformers
ONNX
English
bert
sentence-similarity
text-embeddings-inference
Instructions to use metarank/multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use metarank/multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("metarank/multilingual-e5-small") 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 .gitattributes from metarank/multilingual-e5-small: direct link, hf CLI and curl.
- Browser
- Download file 138 Bytes
-
https://huggingface.co/metarank/multilingual-e5-small/resolve/main/.gitattributes
- Command line
-
hf download hf://metarank/multilingual-e5-small/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/metarank/multilingual-e5-small/resolve/main/.gitattributes
138 Bytes
| *.onnx filter=lfs diff=lfs merge=lfs -text | |
| tokenizer.json filter=lfs diff=lfs merge=lfs -text | |
| *.model filter=lfs diff=lfs merge=lfs -text | |