Instructions to use p1atdev/plat-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use p1atdev/plat-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("p1atdev/plat-diffusion", 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
Commit History
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Add `scale_factor` to vae config. (#5)
- Add `scale_factor` to vae config. (7a308083120b4108700eec7c1692b3d62811fc42) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>ad36c15
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upload v1-3-0 diffusers weights (#1)
- upload v1-3-0 diffusers weights (b20d811cf5190ed17794e54f3ee5a4e59c5e297d)458f2d9
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fix: diffusers
7a650d4 -
version 1.2.1 model
3f43b61
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version 1.0 model
0879f8f
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v0.1
21f7b7d