Instructions to use no3/ridley-at3-beta2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use no3/ridley-at3-beta2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("no3/ridley-at3-beta2", 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
Download vae/diffusion_pytorch_model.bin from no3/ridley-at3-beta2: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/no3/ridley-at3-beta2/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://no3/ridley-at3-beta2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/no3/ridley-at3-beta2/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 26d13927c165757be9e6ca89c2c281427670a254c847a9f544a9d833dea2e646
- Size of remote file:
- 335 MB
- SHA256:
- 7f2ea884fc1c54d80f6f9b4e9864ff7709570cdeea127fb376bf25b9be7b21c9
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