Instructions to use SidXXD/pgd_1-for_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/pgd_1-for_train with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/pgd_1-for_train", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a sks cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_custom_diffusion_weights.bin from SidXXD/pgd_1-for_train: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/pgd_1-for_train/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/pgd_1-for_train/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/pgd_1-for_train/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- ff23d269749e34f628b3d422e4c6db7f74626d516a73dad6a29f19e732879911
- Size of remote file:
- 76.7 MB
- SHA256:
- aa700225c21d36e9f09f4ac26179b502dbf1ac3468b46f27f8d3f29fabaacd11
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