Feature Extraction
sentence-transformers
Safetensors
English
sparse-encoder
sparse
asymmetric
inference-free
splade
Generated from Trainer
dataset_size:18247
loss:SpladeLoss
loss:SparseMultipleNegativesRankingLoss
loss:FlopsLoss
Eval Results (legacy)
Instructions to use oneryalcin/fin-sparse-encoder-doc-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use oneryalcin/fin-sparse-encoder-doc-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("oneryalcin/fin-sparse-encoder-doc-v1") 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:
- 0a2e4fc7255b5bb8e712db77382cff3e8624149075bfb12368ba6dda1f220309
- Size of remote file:
- 122 kB
- SHA256:
- db73ae4c08aa8a138704c73f4314296d6f6fe0e4bc2283d11de954db26f6f159
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