Instructions to use iamthecage/Qwen3-Reranker-0.6B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use iamthecage/Qwen3-Reranker-0.6B-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3-Reranker-0.6B-MLX iamthecage/Qwen3-Reranker-0.6B-MLX
- sentence-transformers
How to use iamthecage/Qwen3-Reranker-0.6B-MLX with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("iamthecage/Qwen3-Reranker-0.6B-MLX") 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
- Local Apps Settings
- LM Studio
README.md exists but content is empty.
- Downloads last month
- 78
Model size
0.6B params
Tensor type
BF16
·
Hardware compatibility
Log In to add your hardware
Quantized
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support