Instructions to use Y-Research-Group/CSRv2-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Y-Research-Group/CSRv2-classification with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Y-Research-Group/CSRv2-classification") 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-classification: direct link, hf CLI and curl.
- Browser
- Download file 52.5 MB
-
https://huggingface.co/Y-Research-Group/CSRv2-classification/resolve/main/3_SparseAutoEncoder/model.safetensors
- Command line
-
hf download hf://Y-Research-Group/CSRv2-classification/3_SparseAutoEncoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Y-Research-Group/CSRv2-classification/resolve/main/3_SparseAutoEncoder/model.safetensors
52.5 MB
- Xet hash:
- 6e07841d7576f55e8636425099fed2c90c2a13061734cc18b4dee439b53e309d
- Size of remote file:
- 52.5 MB
- SHA256:
- cacc40e7f34e96eb314a98fae3cca3780dec5aaac923248e89ed3432bcd439a1
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