Instructions to use diffusers/tiny-stable-diffusion-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/tiny-stable-diffusion-torch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/tiny-stable-diffusion-torch", 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
Commit History
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Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#1)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (7bf728024bad55d6671232d07a990623f2a829c1)c05d787
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Update model_index.json
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Update model_index.json
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Update model_index.json
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Duplicate from hf-internal-testing/tiny-stable-diffusion-torch
Co-authored-by: Anton Lozhkov <anton-l@users.noreply.huggingface.co>79a2ae1