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.py from waltgrace/mlx-expert-sniper: direct link, hf CLI and curl.
- Browser
- Download file 398 Bytes
-
https://huggingface.co/waltgrace/mlx-expert-sniper/resolve/main/setup.py
- Command line
-
hf download hf://waltgrace/mlx-expert-sniper/setup.py
-
curl -L -o setup.py https://huggingface.co/waltgrace/mlx-expert-sniper/resolve/main/setup.py
398 Bytes
| from setuptools import setup, find_packages | |
| setup( | |
| name="mac-tensor", | |
| version="0.1.0", | |
| packages=find_packages(), | |
| package_data={ | |
| "mac_tensor": ["static/*.html", "static/*.css", "static/*.js"], | |
| }, | |
| include_package_data=True, | |
| entry_points={ | |
| "console_scripts": [ | |
| "mac-tensor=mac_tensor.cli:main", | |
| ], | |
| }, | |
| python_requires=">=3.9", | |
| ) | |