Instructions to use edicamargo/any45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use edicamargo/any45 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("edicamargo/any45", 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 edicamargo/any45: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/edicamargo/any45/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://edicamargo/any45@refs/pr/1/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/edicamargo/any45/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- e10ec880e0e98cdc79edff570931fe884fa478c9b31aba92904a6d3349bd3845
- Size of remote file:
- 335 MB
- SHA256:
- 36c26e06ae84ab1082befd28089ff42667329e7d960d434f0c7cb54d0a8f1ed0
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