Image-Text-to-Text
MLX
English
apple-silicon
Mixture of Experts
mixture-of-experts
vision-language
gemma
falcon-perception
inference
Instructions to use waltgrace/mlx-expert-sniper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use waltgrace/mlx-expert-sniper 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("waltgrace/mlx-expert-sniper") config = load_config("waltgrace/mlx-expert-sniper") # 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
Download setup.cfg from waltgrace/mlx-expert-sniper: direct link, hf CLI and curl.
- Browser
- Download file 360 Bytes
-
https://huggingface.co/waltgrace/mlx-expert-sniper/resolve/main/setup.cfg
- Command line
-
hf download hf://waltgrace/mlx-expert-sniper/setup.cfg
-
curl -L -o setup.cfg https://huggingface.co/waltgrace/mlx-expert-sniper/resolve/main/setup.cfg
360 Bytes
| [metadata] | |
| name = mlx-expert-sniper | |
| version = 0.2.0 | |
| [options] | |
| package_dir = | |
| = src | |
| packages = find: | |
| python_requires = >=3.9 | |
| install_requires = | |
| mlx>=0.22.0 | |
| mlx-lm>=0.22.0 | |
| transformers>=4.40.0 | |
| numpy | |
| huggingface-hub | |
| [options.packages.find] | |
| where = src | |
| [options.entry_points] | |
| console_scripts = | |
| mlx-sniper = mlx_expert_sniper.cli:main | |