Sentence Similarity
sentence-transformers
Safetensors
camembert
feature-extraction
dense
Generated from Trainer
dataset_size:14481
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use RavenAgent/devis-matcher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RavenAgent/devis-matcher with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RavenAgent/devis-matcher") sentences = [ "Plomberie sanitaire", "Semis manuel de pelouses à gazon, mauresques et ordinaires", "interne", "Installation sanitaire" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Initial upload: camembert-large fine-tune for French construction matching (v2, 14k pairs)
01590b8 verified - Xet hash:
- 5db261ba86adf0dbc7ff1ad79da54d25fb9878f5ac1fadfab82278d74a688804
- Size of remote file:
- 1.35 GB
- SHA256:
- 851715d3fc932774097c11769a977877f680229bb65961bc6ec23a446d0bdaad
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