Instructions to use hogiahien/aom3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hogiahien/aom3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hogiahien/aom3", 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 unet/diffusion_pytorch_model.bin from hogiahien/aom3: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/hogiahien/aom3/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://hogiahien/aom3/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/hogiahien/aom3/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 040018d6fb8a5fb05857559bf381d1e8eeec0b097072e1ea1f552000e0071241
- Size of remote file:
- 3.44 GB
- SHA256:
- 52dbdfe26ecfe747280ab797f062dc3f43e0c1d1b46e0bea1c4a4897bfe8318a
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