Text Ranking
sentence-transformers
Safetensors
multilingual
xlm-roberta
cross-encoder
reranker
cross-lingual
text-embeddings-inference
Instructions to use nlpai-lab/LAMAR-600m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nlpai-lab/LAMAR-600m with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("nlpai-lab/LAMAR-600m") 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
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