Instructions to use ekhalavyan/sdxl-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ekhalavyan/sdxl-vae with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ekhalavyan/sdxl-vae", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download diffusion_flax_model.msgpack from ekhalavyan/sdxl-vae: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/ekhalavyan/sdxl-vae/resolve/main/diffusion_flax_model.msgpack
- Command line
-
hf download hf://ekhalavyan/sdxl-vae/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/ekhalavyan/sdxl-vae/resolve/main/diffusion_flax_model.msgpack
335 MB
- Xet hash:
- e06ee69185545caa99b4363b69c430402ba35e263c0f63c379e1697a6939e2dc
- Size of remote file:
- 335 MB
- SHA256:
- 1857495e1d4e28140013764ffd620f6aa1fb0311dd43d7cf083f72704c69e3ee
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