Text Ranking
sentence-transformers
Safetensors
bert
reranker
cross-encoder
multilingual
cross-lingual
government
indian-languages
reranking
e5
text-embeddings-inference
Instructions to use quanfire-ai/rerank-gov-indic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use quanfire-ai/rerank-gov-indic with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("quanfire-ai/rerank-gov-indic") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
Ctrl+K
Publish rerank-gov-indic v1.0.0: cross-lingual government reranker (semi-hard negatives, +31.9% R@1 over embed-gov-indic)
02d446d verified