Instructions to use matgu23/try-1-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use matgu23/try-1-0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("matgu23/try-1-0", 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
- Xet hash:
- 88b1a00ab222654e2645daee7a794f8a5dd6ab31e67865e5c80c0e925540e2bf
- Size of remote file:
- 246 MB
- SHA256:
- 18d7ee488d9db72db4bf29d022666b1a5590fcf39508e61266c892ee9c42f3de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.