Sentence Similarity
sentence-transformers
Safetensors
Transformers
French
English
Bilingual
feature-extraction
french
english
sentence-embedding
mteb
custom_code
Eval Results (legacy)
Instructions to use dangvantuan/french-document-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dangvantuan/french-document-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dangvantuan/french-document-embedding", trust_remote_code=True) 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] - Transformers
How to use dangvantuan/french-document-embedding with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dangvantuan/french-document-embedding", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from dangvantuan/french-document-embedding: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/dangvantuan/french-document-embedding/resolve/main/model.safetensors
- Command line
-
hf download hf://dangvantuan/french-document-embedding/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/dangvantuan/french-document-embedding/resolve/main/model.safetensors
1.22 GB
- Xet hash:
- 93376fc6e64fee4599b95017e0aa36806ca386ea938d9150af403cbaad445dee
- Size of remote file:
- 1.22 GB
- SHA256:
- 433c60b1e43c8b998ae20dc5967c16764f9b2737252a6d14ba0bf3efccfaac2a
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