Feature Extraction
sentence-transformers
Safetensors
English
bert
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:1200000
loss:SpladeLoss
loss:SparseMarginMSELoss
loss:FlopsLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use rasyosef/splade-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/splade-tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rasyosef/splade-tiny") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8522a5a8c8bf3ca8322e08f91d460b408cfad7772af6bce2dffea25f7a174e9
- Size of remote file:
- 17.7 MB
- SHA256:
- 6b234281fbc722918304ccf3e74f1b216cc2deb2c3197034a6bf90f2a6b7e3fe
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