Text Ranking
sentence-transformers
Safetensors
cross-encoder
reranker
Generated from Trainer
dataset_size:342614
loss:BinaryCrossEntropyLoss
custom_code
Eval Results (legacy)
Instructions to use cuadron11/jina-reranker-v2-base-multilingual-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cuadron11/jina-reranker-v2-base-multilingual-binary with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("cuadron11/jina-reranker-v2-base-multilingual-binary", trust_remote_code=True) 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
Download tokenizer.json from cuadron11/jina-reranker-v2-base-multilingual-binary: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/cuadron11/jina-reranker-v2-base-multilingual-binary/resolve/main/tokenizer.json
- Command line
-
hf download hf://cuadron11/jina-reranker-v2-base-multilingual-binary/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/cuadron11/jina-reranker-v2-base-multilingual-binary/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 2bf012789e5894caa5988dd00f5b8614020373ecd4fefa1d028e4d67d3e97e9e
- Size of remote file:
- 17.1 MB
- SHA256:
- e802fe5337779428818439760a1e6161ed36ceed72d4ebcbda9c139a2108fc99
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