Instructions to use CCMat/ddpm-bored-apes-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CCMat/ddpm-bored-apes-128 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CCMat/ddpm-bored-apes-128", 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
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README.md
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@@ -20,3 +20,5 @@ pipeline = DDPMPipeline.from_pretrained('CCMat/diff-bored-apes-128')
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image = pipeline().images[0]
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image
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```
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image = pipeline().images[0]
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image
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```
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## Samples
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