Feature Extraction
sentence-transformers
Safetensors
French
camembert
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:483497
loss:SpladeLoss
loss:SparseMarginMSELoss
loss:FlopsLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use sparse-encoder/splade-camembert-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sparse-encoder/splade-camembert-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sparse-encoder/splade-camembert-base-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cf6f846493e11989d1899d00e27d90754b4a8e7207ea4817fb3ebae1ccb3f1f
- Size of remote file:
- 443 MB
- SHA256:
- aef2cd382cb34fcc069a15957e39819bc3c674294908baf77b53cab5fb8cb58a
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