Instructions to use tiddu/all_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiddu/all_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tiddu/all_models", 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 vae_approx/taesdxl_decoder.pth from tiddu/all_models: direct link, hf CLI and curl.
- Browser
- Download file 4.92 MB
-
https://huggingface.co/tiddu/all_models/resolve/main/vae_approx/taesdxl_decoder.pth
- Command line
-
hf download hf://tiddu/all_models/vae_approx/taesdxl_decoder.pth
-
curl -L -o taesdxl_decoder.pth https://huggingface.co/tiddu/all_models/resolve/main/vae_approx/taesdxl_decoder.pth
4.92 MB
- Xet hash:
- 8067ad84794b77b72eda728f4d31672cc042421de03908df1faf9dc5bdc5bbc4
- Size of remote file:
- 4.92 MB
- SHA256:
- e68e771b88ec0278a3b306d8e0fd1c7448471fb91035a842d899e14390303587
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