Instructions to use SidXXD/pgd_2-dds_clip-for_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/pgd_2-dds_clip-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_2-dds_clip-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_2-dds_clip-for_train: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/pgd_2-dds_clip-for_train/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/pgd_2-dds_clip-for_train/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/pgd_2-dds_clip-for_train/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- 754eefc0a8f70ed4103134a6efa833102c43123d2d7c93d5649c17e6dd30789d
- Size of remote file:
- 76.7 MB
- SHA256:
- 4ab30489e0295143a720366ca706f283ac22695f00bc6155bf2850ded7815399
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