Instructions to use peter168/ddpm-floorplans_tutorial-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use peter168/ddpm-floorplans_tutorial-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("peter168/ddpm-floorplans_tutorial-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
Upload model
Browse files- config.json +1 -1
- diffusion_pytorch_model.safetensors +1 -1
config.json
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"_class_name": "UNet2DModel",
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"_diffusers_version": "0.
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"act_fn": "silu",
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"add_attention": true,
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"attention_head_dim": 8,
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"_class_name": "UNet2DModel",
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"_diffusers_version": "0.27.2",
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"act_fn": "silu",
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"add_attention": true,
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"attention_head_dim": 8,
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e541eeffd491ac3642274a1720320ddb95ad0f440479ed87eeaac70b3dcd83f1
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size 454741108
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