Instructions to use stabilityai/sdxl-turbo_amdgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stabilityai/sdxl-turbo_amdgpu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo_amdgpu", 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
Update unet model data name to standard
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by owenzhangzhengzhong - opened
stable-diffusion-xl-turbo-io32/unet/model.onnx
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ace30d89639ffa02fb80f585880924e7e76d4a019968bdff34d90a3aac3418f
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size 1403642
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stable-diffusion-xl-turbo-io32/unet/{c74fd389-f55d-11ef-8a5e-f0a65413afc1 → model.onnx.data}
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File without changes
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