Instructions to use BackTo2014/DDPM-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BackTo2014/DDPM-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BackTo2014/DDPM-test", 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
Update config.json
Browse files- config.json +3 -3
config.json
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"DownBlock2D"
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],
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"up_block_types": [
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"AttnUpBlock2D",
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"block_out_channels": [
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128, 256, 256, 256
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"DownBlock2D"
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],
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"up_block_types": [
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"UpBlock2D",
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"AttnUpBlock2D",
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"UpBlock2D",
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"UpBlock2D"
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],
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"block_out_channels": [
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128, 256, 256, 256
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