Sentence Similarity
sentence-transformers
PyTorch
Safetensors
French
flaubert
Text
Sentence Similarity
Sentence-Embedding
camembert-base
Eval Results (legacy)
Instructions to use Lajavaness/sentence-flaubert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Lajavaness/sentence-flaubert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Lajavaness/sentence-flaubert-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] - Inference
- Notebooks
- Google Colab
- Kaggle
Download sentence_bert_config.json from Lajavaness/sentence-flaubert-base: direct link, hf CLI and curl.
- Browser
- Download file 52 Bytes
-
https://huggingface.co/Lajavaness/sentence-flaubert-base/resolve/refs%2Fpr%2F2/sentence_bert_config.json
- Command line
-
hf download hf://Lajavaness/sentence-flaubert-base@refs/pr/2/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/Lajavaness/sentence-flaubert-base/resolve/refs%2Fpr%2F2/sentence_bert_config.json
52 Bytes
| { | |
| "max_seq_length": 512, | |
| "do_lower_case": true | |
| } |