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
Download text_encoder/model.onnx from amd/stable-diffusion-1.5_io32_amdgpu: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/amd/stable-diffusion-1.5_io32_amdgpu/resolve/refs%2Fpr%2F5/text_encoder/model.onnx
- Command line
-
hf download hf://amd/stable-diffusion-1.5_io32_amdgpu@refs/pr/5/text_encoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/amd/stable-diffusion-1.5_io32_amdgpu/resolve/refs%2Fpr%2F5/text_encoder/model.onnx
246 MB
- Xet hash:
- 5fc416a8c986fd37656225c80412eb825f796d50f2825ca057fffb96d4be85ba
- Size of remote file:
- 246 MB
- SHA256:
- 2b2064aafacab7abdae3f61b32a213d8c3c5a62a786b0c90552a3c61c80d4141
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