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 samples/cabin_upstream.png from kingjones777/Ming-Image-0.1-Design-ROCm-INT8: direct link, hf CLI and curl.
- Browser
- Download file 1.65 MB
-
https://huggingface.co/kingjones777/Ming-Image-0.1-Design-ROCm-INT8/resolve/main/samples/cabin_upstream.png
- Command line
-
hf download hf://kingjones777/Ming-Image-0.1-Design-ROCm-INT8/samples/cabin_upstream.png
-
curl -L -o cabin_upstream.png https://huggingface.co/kingjones777/Ming-Image-0.1-Design-ROCm-INT8/resolve/main/samples/cabin_upstream.png
1.65 MB

- Xet hash:
- 64c4038b9fea27fdc6afcfc7e94833dabecd8dbba1c836e92491270524f5f7bc
- Size of remote file:
- 1.65 MB
- SHA256:
- 1c9aaa45455f78c289bc41d8aa175cc4e01c46b1c57e109be043b9f78de57bc1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.