Instructions to use emilianJR/Anyh91 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use emilianJR/Anyh91 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("emilianJR/Anyh91", 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 emilianJR/Anyh91: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/emilianJR/Anyh91/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://emilianJR/Anyh91/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/emilianJR/Anyh91/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 0e437b4171434c81087cabd7d5eee6d00326c155dc70322b98e5a557d855cc17
- Size of remote file:
- 335 MB
- SHA256:
- 7467947f421997b6c211cf78233ec9c3378fd494d6c9491d6f4ea2b07282a4fc
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