Instructions to use matgu23/ptn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use matgu23/ptn 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/ptn", 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:
- d6340779023522d0a3cd0b4b9e7009a4ef39a19d69300e348317dbece4ba3f42
- Size of remote file:
- 246 MB
- SHA256:
- 9c54a0020c71fd4beff5e2e50d2c91d8a38a891d692ba57fdcd2966c9bd26c16
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