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 pyproject.toml from waltgrace/mlx-expert-sniper: direct link, hf CLI and curl.
- Browser
- Download file 573 Bytes
-
https://huggingface.co/waltgrace/mlx-expert-sniper/resolve/main/pyproject.toml
- Command line
-
hf download hf://waltgrace/mlx-expert-sniper/pyproject.toml
-
curl -L -o pyproject.toml https://huggingface.co/waltgrace/mlx-expert-sniper/resolve/main/pyproject.toml
573 Bytes
| [build-system] | |
| requires = ["setuptools>=68.0", "wheel"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "mac-tensor" | |
| version = "0.1.0" | |
| description = "Distributed MoE inference across multiple Macs" | |
| readme = "README.md" | |
| license = {text = "MIT"} | |
| requires-python = ">=3.9" | |
| dependencies = [ | |
| "mlx>=0.22.0", | |
| "mlx-lm>=0.22.0", | |
| "numpy", | |
| "fastapi", | |
| "uvicorn", | |
| "requests", | |
| "transformers", | |
| "tokenizers", | |
| "huggingface_hub", | |
| ] | |
| [project.scripts] | |
| mac-tensor = "mac_tensor.cli:main" | |
| [tool.setuptools.packages.find] | |
| include = ["mac_tensor*"] | |