Instructions to use OzzyGT/ming_image_custom_blocks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OzzyGT/ming_image_custom_blocks with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OzzyGT/ming_image_custom_blocks", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download modular_model_index.json from OzzyGT/ming_image_custom_blocks: direct link, hf CLI and curl.
- Browser
- Download file 82 Bytes
-
https://huggingface.co/OzzyGT/ming_image_custom_blocks/resolve/main/modular_model_index.json
- Command line
-
hf download hf://OzzyGT/ming_image_custom_blocks/modular_model_index.json
-
curl -L -o modular_model_index.json https://huggingface.co/OzzyGT/ming_image_custom_blocks/resolve/main/modular_model_index.json
82 Bytes
| { | |
| "_class_name": "ModularPipeline", | |
| "_blocks_class_name": "MingImageBlocks" | |
| } | |