Instructions to use CompVis/stable-diffusion-v1-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/stable-diffusion-v1-1 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/stable-diffusion-v1-1", 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
- Local Apps
- Draw Things
- DiffusionBee
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3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
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Please read the full license here: https://huggingface.co/spaces/CompVis/stable-diffusion-license
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By clicking on "Access repository" below, you accept that your *contact information* (email address and username) can be shared with the model authors as well:
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extra_gated_fields:
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I have read the License and agree with its terms: checkbox
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3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
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Please read the full license here: https://huggingface.co/spaces/CompVis/stable-diffusion-license
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By clicking on "Access repository" below, you accept that your *contact information* (email address and username) can be shared with the model authors as well:
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extra_gated_fields:
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I have read the License and agree with its terms: checkbox
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