Sentence Similarity
sentence-transformers
Safetensors
French
xlm-roberta
passage-retrieval
pruned
text-embeddings-inference
Instructions to use aureliend/french-multilingual-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use aureliend/french-multilingual-e5-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aureliend/french-multilingual-e5-large") sentences = [ "C'est une personne heureuse", "C'est un chien heureux", "C'est une personne très heureuse", "Aujourd'hui est une journée ensoleillée" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from aureliend/french-multilingual-e5-large: direct link, hf CLI and curl.
- Browser
- Download file 201 Bytes
-
https://huggingface.co/aureliend/french-multilingual-e5-large/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://aureliend/french-multilingual-e5-large/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/aureliend/french-multilingual-e5-large/resolve/main/1_Pooling/config.json
201 Bytes
| { | |
| "word_embedding_dimension": 1024, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false | |
| } |