Model Details
Full Model IDhotchpotch/japanese-reranker-cross-encoder-small-v1
Pipeline / Tasktext-ranking
Librarysentence-transformers
Downloads (all-time)250.5K
Likes5
Last Modified7/9/2025
Author / Orghotchpotch
PrivateNo � public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-ranking", model="hotchpotch/japanese-reranker-cross-encoder-small-v1")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
sentence-transformerssafetensorsxlm-robertatext-rankingjadataset:hotchpotch/JQaRAdataset:shunk031/JGLUEdataset:miracl/miracldataset:castorini/mr-tydidataset:unicamp-dl/mmarcolicense:mittext-embeddings-inferenceendpoints_compatibleregion:us
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This model is designed for the text-ranking task. Explore more models for this use case.
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⬇ Downloads250.5K
����� Community Likes5
🛠�� Requirements
- →Install: pip install sentence-transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.