Instructions to use mlx-community/Qwen3-VL-Reranker-2B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/Qwen3-VL-Reranker-2B-4bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mlx-community/Qwen3-VL-Reranker-2B-4bit") model = AutoModelForMultimodalLM.from_pretrained("mlx-community/Qwen3-VL-Reranker-2B-4bit", device_map="auto") - MLX
How to use mlx-community/Qwen3-VL-Reranker-2B-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/Qwen3-VL-Reranker-2B-4bit --local-dir Qwen3-VL-Reranker-2B-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from mlx-community/Qwen3-VL-Reranker-2B-4bit: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/mlx-community/Qwen3-VL-Reranker-2B-4bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://mlx-community/Qwen3-VL-Reranker-2B-4bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mlx-community/Qwen3-VL-Reranker-2B-4bit/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- dde3c5a4d468da6fe61f11ffa8f04af2d101f8f4a0fe118c37bd31bb8c3017b6
- Size of remote file:
- 11.4 MB
- SHA256:
- be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
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