Visual Question Answering
Transformers
Safetensors
MLX
English
qwen2_5_vl
image-text-to-text
multimodal
text-generation-inference
Instructions to use mlx-community/VL-Rethinker-7B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/VL-Rethinker-7B-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="mlx-community/VL-Rethinker-7B-4bit")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mlx-community/VL-Rethinker-7B-4bit") model = AutoModelForMultimodalLM.from_pretrained("mlx-community/VL-Rethinker-7B-4bit", device_map="auto") - MLX
How to use mlx-community/VL-Rethinker-7B-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir VL-Rethinker-7B-4bit mlx-community/VL-Rethinker-7B-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- be1231ff4ca03e7a1b7b36074fce04cf35f636583777f7359d331015e520bdb5
- Size of remote file:
- 4.87 GB
- SHA256:
- 9f64652b41f5a19788318f7d76d7ea223dfe16c9eac8479095b5adc98a36360d
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