Instructions to use google/ddpm-cifar10-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use google/ddpm-cifar10-32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("google/ddpm-cifar10-32", 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
Commit History
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Adding `safetensors` variant of this model (#14)
- Adding `safetensors` variant of this model (30eb34ce06e995c15ec349bc188a86d6bd0d5359) Co-authored-by: Steven Liu <stevhliu@users.noreply.huggingface.co>267b167
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Fix broken link for inference example (#9)
- Fix broken link for inference example (f787a9fcf36fb132304a942199b94432982ed011) Co-authored-by: Max Shen <mxwsn@users.noreply.huggingface.co>16ad61f
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Upload README.md with huggingface_hub (#8)
- Upload README.md with huggingface_hub (93391438beb71bc1810fb80fb8be473945a1c4fe)0b9e450 -
Merge branch 'main' of https://huggingface.co/google/ddpm-cifar10-32 into main
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rem image
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Upload images with huggingface_hub (#1)
- Upload images with huggingface_hub (39cc2524c6bdb73517ac48d0c6f49b976e8dc0ba) Co-authored-by: Arthur Zucker <ArthurZ@users.noreply.huggingface.co>a90a1ab -
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convert weights
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Pipeline files
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