Instructions to use nervouslyopen/Qwen2.5-VL-3B-Instruct-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use nervouslyopen/Qwen2.5-VL-3B-Instruct-4bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("nervouslyopen/Qwen2.5-VL-3B-Instruct-4bit") config = load_config("nervouslyopen/Qwen2.5-VL-3B-Instruct-4bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- bcb070f5dfb1551c12c4d077c4dbb8e34b2b44a8959ad345bd309b72554bb123
- Size of remote file:
- 3.07 GB
- SHA256:
- d6c75f366b0c54a328b8d64a5458a863cb6102646c8d885015c010f7e4d3ad4c
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