Text Ranking
Transformers
Safetensors
English
bert
text-classification
reranker
cross-encoder
legal
statute
retrieval
e5
text-embeddings-inference
Instructions to use quanfire-ai/rerank-statute-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quanfire-ai/rerank-statute-en with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("quanfire-ai/rerank-statute-en") model = AutoModelForSequenceClassification.from_pretrained("quanfire-ai/rerank-statute-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Publish rerank-statute-en v1.0.0: first Quanfire reranker — statute cross-encoder (+63.8% R@1, CI excludes 0)
c48f850 verified - Xet hash:
- 95b6f9f4bd916e1539f8958c5d6089b29b29ef87dc55871ff2aa075ce29b5329
- Size of remote file:
- 17.1 MB
- SHA256:
- 2b95ee17661f8dfbbceaba374f6d277a6b5d8e1898c070a16331622024f58c67
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