Text Classification
sentence-transformers
PyTorch
ONNX
Safetensors
English
Chinese
mteb
text-embeddings-inference
Eval Results (legacy)
Instructions to use Karmukilan/bge-reranker-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Karmukilan/bge-reranker-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Karmukilan/bge-reranker-base") 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:
- d2112a1b0c434257826d0a27b7a17ead70c12a4f5b566c7ad8fbcd4e0b1c13e3
- Size of remote file:
- 799 Bytes
- SHA256:
- 289adf7ada1eb6b4afa7589a48a032d45a076cf2e46dcdb3b4cabc33be14f708
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