Instructions to use amd/stable-diffusion-1.5_io32_amdgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use amd/stable-diffusion-1.5_io32_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("amd/stable-diffusion-1.5_io32_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
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README.md
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## _io32/16
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_io32: model input is fp32, model will convert the input to fp16, perform ops in fp16 and write the final result in fp32
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_io16: model input is fp16, perform ops in fp16 and write the final result in fp16
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## How to Get Started with the Model
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## _io32/16
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_io32: model input is fp32, model will convert the input to fp16, perform ops in fp16 and write the final result in fp32
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_io16: model input is fp16, perform ops in fp16 and write the final result in fp16
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## How to Get Started with the Model
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