Model Details
Full Model IDhotchpotch/japanese-reranker-cross-encoder-small-v1
Pipeline / Tasktext-ranking
Librarysentence-transformers
Downloads (all-time)645.0K
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
More text-ranking Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: text-ranking
This model is designed for the text-ranking task. Explore more models for this use case.
All text-ranking Models →📊 Popularity
⬇ Downloads645.0K
❤️ 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.