Instructions to use Abe13/bge-reranker-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abe13/bge-reranker-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Abe13/bge-reranker-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Abe13/bge-reranker-base") model = AutoModel.from_pretrained("Abe13/bge-reranker-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b3b599c94949c685c78b4f5db65f8c53ace5bb64a64a7332527bb3d8872d82e
- Size of remote file:
- 17.1 MB
- SHA256:
- 67f58df22db42114222e4c5a0876a7c9fbd984720682c9960c0d03775ce4d317
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