Instructions to use kpsss34/Pre-train_diffusion_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kpsss34/Pre-train_diffusion_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kpsss34/Pre-train_diffusion_models", 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
- Xet hash:
- e5c7b830f9dae696647890589ace51f0378643d3ab30a0dd3cff2147d0093d2c
- Size of remote file:
- 11.9 GB
- SHA256:
- 76e03744d0423d1201332f19d3f2402bd4c5d63752f683fc8b92c72c24457bda
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