Instructions to use stabilityai/stable-diffusion-3.5-large-turbo_amdgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stabilityai/stable-diffusion-3.5-large-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/stable-diffusion-3.5-large-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 (#2)
Browse files- Update unet model data name to standard (f3a2d96657498e912f44d1b9ae3a75fadbeeff22)
stable-diffusion-3-5-large-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 sha256:03cebacb95c101dd68b2f4ee1d6e0d6662eb774be6c31145d57601e5f8094c95
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size 3634824
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stable-diffusion-3-5-large-turbo_io32/unet/{5af4585c-efd6-11ef-ad04-782b46b46a44 → model.onnx.data}
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File without changes
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