Instructions to use CompVis/ldm-celebahq-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/ldm-celebahq-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/ldm-celebahq-256", 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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upload new weights
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add new config
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Update README.md
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Move images
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Update model_index.json
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convert weights
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finish config
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update config
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Update README.md
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Update README.md
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Update README.md
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Update README.md
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correct readme
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Merge branch 'main' of https://huggingface.co/CompVis/latent-diffusion-celeba-256 into main
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clamp generated images
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Update README.md
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Update README.md
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Create README.md
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new images
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correct model
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upload 0 images
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finalize
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some more images
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new image
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change image processing
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next try
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add pipeline and give image a 2nd try
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[Celeba-256] Upload first model
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initial commit
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