Instructions to use GraydientPlatformAPI/mucha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/mucha with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GraydientPlatformAPI/mucha", 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 text_encoder/model.safetensors from GraydientPlatformAPI/mucha: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/GraydientPlatformAPI/mucha/resolve/main/text_encoder/model.safetensors
- Command line
-
hf download hf://GraydientPlatformAPI/mucha/text_encoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/GraydientPlatformAPI/mucha/resolve/main/text_encoder/model.safetensors
246 MB
- Xet hash:
- d6a10abe789c5176d72f7582d1e88582fb4c741d5820f257d920a9d2e4aa074b
- Size of remote file:
- 246 MB
- SHA256:
- c720ba7c9438896c8ffda7d528673815e521e9284bee351fa6c84909bde8b16a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.