Instructions to use aarabil/bge-reranker-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aarabil/bge-reranker-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aarabil/bge-reranker-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aarabil/bge-reranker-base") model = AutoModelForSequenceClassification.from_pretrained("aarabil/bge-reranker-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf49ce6af52b15db4d575c972f011c1a90de213c47df18035b8f2fd4ed1b1e7c
- Size of remote file:
- 17.1 MB
- SHA256:
- 14917dd757b81bc44d4af6b028367351702656670c1954e055dabdfcf21593cf
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