Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:5616
loss:BinaryCrossEntropyLoss
text-embeddings-inference
Instructions to use voIsung/bge-reranker-cvjd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use voIsung/bge-reranker-cvjd with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("voIsung/bge-reranker-cvjd") 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
File size: 133 Bytes
1f8d6e5 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4a8d0b7573869188be52cca17a27a84f3cfbc0a5536c28ee1eca82903e8c68c6
size 17083051
|