Sentence Similarity
sentence-transformers
Safetensors
French
camembert
Text
Sentence Similarity
Sentence-Embedding
camembert-base
Eval Results (legacy)
text-embeddings-inference
Instructions to use Saegus/sentence-camembert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Saegus/sentence-camembert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Saegus/sentence-camembert-base") 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
Add model context in README
Browse files
README.md
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library_name: sentence-transformers
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---
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## Pre-trained sentence embedding models are the state-of-the-art of Sentence Embeddings for French.
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Model is Fine-tuned using pre-trained [facebook/camembert-base](https://huggingface.co/camembert/camembert-base) and
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[Siamese BERT-Networks with 'sentences-transformers'](https://www.sbert.net/) on dataset [stsb](https://huggingface.co/datasets/stsb_multi_mt/viewer/fr/train)
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author={Martin, Louis and Muller, Benjamin and Su{\'a}rez, Pedro Javier Ortiz and Dupont, Yoann and Romary, Laurent and de la Clergerie, {\'E}ric Villemonte and Seddah, Djam{\'e} and Sagot, Beno{\^\i}t},
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journal={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
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year={2020}
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}
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library_name: sentence-transformers
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---
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## sentence-camembert-base
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Model is loaded from [dangvantuan/sentence-camembert-base](https://huggingface.co/dangvantuan/sentence-camembert-base).
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---
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## Pre-trained sentence embedding models are the state-of-the-art of Sentence Embeddings for French.
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Model is Fine-tuned using pre-trained [facebook/camembert-base](https://huggingface.co/camembert/camembert-base) and
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[Siamese BERT-Networks with 'sentences-transformers'](https://www.sbert.net/) on dataset [stsb](https://huggingface.co/datasets/stsb_multi_mt/viewer/fr/train)
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author={Martin, Louis and Muller, Benjamin and Su{\'a}rez, Pedro Javier Ortiz and Dupont, Yoann and Romary, Laurent and de la Clergerie, {\'E}ric Villemonte and Seddah, Djam{\'e} and Sagot, Beno{\^\i}t},
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journal={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
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year={2020}
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}
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