Instructions to use Y-Research-Group/CSRv2-reranking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Y-Research-Group/CSRv2-reranking with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Y-Research-Group/CSRv2-reranking") 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
Download 3_SparseAutoEncoder/model.safetensors from Y-Research-Group/CSRv2-reranking: direct link, hf CLI and curl.
- Browser
- Download file 52.5 MB
-
https://huggingface.co/Y-Research-Group/CSRv2-reranking/resolve/main/3_SparseAutoEncoder/model.safetensors
- Command line
-
hf download hf://Y-Research-Group/CSRv2-reranking/3_SparseAutoEncoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Y-Research-Group/CSRv2-reranking/resolve/main/3_SparseAutoEncoder/model.safetensors
52.5 MB
- Xet hash:
- a03c75c82097d6c1b0472c6f934c226763c380503d0b176cb091837a45b4474d
- Size of remote file:
- 52.5 MB
- SHA256:
- 7ce64a27922a2036e3423591c71d64aa3e77a567ea4339eb4da165369f95a4da
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