Instructions to use kingjones777/Ming-Image-0.1-Design-ROCm-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kingjones777/Ming-Image-0.1-Design-ROCm-INT8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kingjones777/Ming-Image-0.1-Design-ROCm-INT8", 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 code/examples/profiles/generation_edit.json from kingjones777/Ming-Image-0.1-Design-ROCm-INT8: direct link, hf CLI and curl.
- Browser
- Download file 200 Bytes
-
https://huggingface.co/kingjones777/Ming-Image-0.1-Design-ROCm-INT8/resolve/main/code/examples/profiles/generation_edit.json
- Command line
-
hf download hf://kingjones777/Ming-Image-0.1-Design-ROCm-INT8/code/examples/profiles/generation_edit.json
-
curl -L -o generation_edit.json https://huggingface.co/kingjones777/Ming-Image-0.1-Design-ROCm-INT8/resolve/main/code/examples/profiles/generation_edit.json
200 Bytes
| { | |
| "schema_version": 1, | |
| "inference_profile": "generation_edit", | |
| "alignment_padding_mode": "zero_masked", | |
| "multi_frame_output": false, | |
| "vae_input_channels": 4, | |
| "vae_sample_mode": "argmax" | |
| } | |