Image-Text-to-Text
MLX
Safetensors
English
qwen2_5_vl
multimodal
gui
gui-agent
ui-tars
conversational
8-bit precision
Instructions to use mlx-community/UI-TARS-1.5-7B-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/UI-TARS-1.5-7B-8bit 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("mlx-community/UI-TARS-1.5-7B-8bit") config = load_config("mlx-community/UI-TARS-1.5-7B-8bit") # 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
- LM Studio
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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