Instructions to use madebyollin/sdxl-vae-fp16-fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use madebyollin/sdxl-vae-fp16-fix 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/sdxl-vae-fp16-fix", 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
attempt at a1111 instructions
Browse files
README.md
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## Details
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SDXL-VAE generates NaNs in fp16 because the internal activation values are too big:
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## Automatic1111 Usage
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1. Download the fixed [sdxl.vae.safetensors](https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/resolve/main/sdxl.vae.safetensors?download=true) file
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2. Move this `sdxl.vae.safetensors` file into the webui folder under `stable-diffusion-webui/models/VAE`
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3. In your webui settings, select the fixed VAE you just added
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4. If you were using the `--no-half-vae` command line arg for SDXL (in `webui-user.bat` or wherever), you can now remove it
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(Disclaimer - I haven't tested this, just aggregating various instructions I've seen elsewhere :P PRs to improve these instructions are welcomed!)
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## Details
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SDXL-VAE generates NaNs in fp16 because the internal activation values are too big:
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