Text Classification
sentence-transformers
Safetensors
English
bert
cross-encoder
biomedical
gene-disease
Gene2Phenotype
LitDD
text-embeddings-inference
Instructions to use tmy100000001/LitDD_crossencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tmy100000001/LitDD_crossencoder with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("tmy100000001/LitDD_crossencoder") 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
model card: revised pipeline is screen -> gene gate -> LLM; cross-encoder off the critical path
9c99efb verified