Instructions to use hlky/tiny-sdxl-custom-components-automodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hlky/tiny-sdxl-custom-components-automodel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hlky/tiny-sdxl-custom-components-automodel", 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_decoder/model.onnx from hlky/tiny-sdxl-custom-components-automodel: direct link, hf CLI and curl.
- Browser
- Download file 1.68 MB
-
https://huggingface.co/hlky/tiny-sdxl-custom-components-automodel/resolve/main/vae_decoder/model.onnx
- Command line
-
hf download hf://hlky/tiny-sdxl-custom-components-automodel/vae_decoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/hlky/tiny-sdxl-custom-components-automodel/resolve/main/vae_decoder/model.onnx
1.68 MB
- Xet hash:
- 1b6e34613a1261d3f28062632d64d8c020e1a0bca1a4a75c56853b496dafeb7f
- Size of remote file:
- 1.68 MB
- SHA256:
- 6d43e163a98640b88a7fc09bdab4ce4e94dd14eb9d75405d3cd78704484c12de
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