Model Details
Full Model IDggml-org/Qwen3-Reranker-0.6B-Q8_0-GGUF
Pipeline / Tasktext-ranking
Librarytransformers
Downloads (all-time)105.3K
Likes29
Last Modified10/3/2025
Author / Orgggml-org
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="ggml-org/Qwen3-Reranker-0.6B-Q8_0-GGUF")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformersggufllama-cppgguf-my-repotext-rankingbase_model:Qwen/Qwen3-Reranker-0.6Bbase_model:quantized:Qwen/Qwen3-Reranker-0.6Blicense:apache-2.0endpoints_compatibleregion:usconversational
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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.
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⬇ Downloads105.3K
❤️ Community Likes29
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.