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:
# 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
File size: 349 Bytes
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