Instructions to use madebyollin/taesd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use madebyollin/taesd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("madebyollin/taesd", 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
Download diffusion_pytorch_model.bin from madebyollin/taesd: direct link, hf CLI and curl.
- Browser
- Download file 9.82 MB
-
https://huggingface.co/madebyollin/taesd/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://madebyollin/taesd/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/madebyollin/taesd/resolve/main/diffusion_pytorch_model.bin
9.82 MB
- Xet hash:
- ff1e318ad7757178660d86105f21754f6a871b56ef23a76151cc6a625aa50c59
- Size of remote file:
- 9.82 MB
- SHA256:
- 5fd7edbf16d049365dda1dfd6df71526dc1b24ce78537dcad733f7b73921d267
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