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:
- 30ec70918fc25930f584436129a94ca937e68b05ccaa5a0fa513b2a469896d47
- Size of remote file:
- 443 Bytes
- SHA256:
- a1d6bc8734a6f635dc158508bef000f8e2e5a759c7d92f984b2c86e5ff53425b
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