Text-to-Image
MLX
Safetensors
English
Chinese
moss_image
apple-silicon
moss-image
text-rendering
layout
quantized
8-bit precision
Instructions to use VisualInference/MOSS-Image-SFT-MLX-compact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use VisualInference/MOSS-Image-SFT-MLX-compact with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download VisualInference/MOSS-Image-SFT-MLX-compact --local-dir MOSS-Image-SFT-MLX-compact
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download config.json from VisualInference/MOSS-Image-SFT-MLX-compact: direct link, hf CLI and curl.
- Browser
- Download file 350 Bytes
-
https://huggingface.co/VisualInference/MOSS-Image-SFT-MLX-compact/resolve/main/config.json
- Command line
-
hf download hf://VisualInference/MOSS-Image-SFT-MLX-compact/config.json
-
curl -L -o config.json https://huggingface.co/VisualInference/MOSS-Image-SFT-MLX-compact/resolve/main/config.json
350 Bytes
| { | |
| "model_type": "moss_image", | |
| "library_name": "moss-image-mlx", | |
| "format": 1, | |
| "tier": "compact", | |
| "source_model": "OpenMOSS-Team/MOSS-Image-SFT", | |
| "transformer_quantization": "affine8g64", | |
| "text_encoder_quantization": "affine6g64", | |
| "components": [ | |
| "transformer", | |
| "text_encoder", | |
| "tokenizer", | |
| "vae", | |
| "scheduler" | |
| ] | |
| } | |