Feature Extraction
sentence-transformers
Safetensors
French
camembert
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:12227
loss:SpladeLoss
loss:SparseCosineSimilarityLoss
loss:FlopsLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use CATIE-AQ/SPLADE_camembert-base_STS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use CATIE-AQ/SPLADE_camembert-base_STS with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("CATIE-AQ/SPLADE_camembert-base_STS") queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
Ctrl+K