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_encoder.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_encoder.pth
- Command line
-
hf download hf://tiddu/all_models/vae_approx/taesdxl_encoder.pth
-
curl -L -o taesdxl_encoder.pth https://huggingface.co/tiddu/all_models/resolve/main/vae_approx/taesdxl_encoder.pth
4.92 MB
- Xet hash:
- 6a563e3ca3c62ea85369598f482ec9f7a0555d465bbbd1828ea3924010622ce0
- Size of remote file:
- 4.92 MB
- SHA256:
- d32e529e67a1f3152afcf755dc1360b221421c988d7eeb6a8a8c8a839432a989
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