Instructions to use nitrosocke/redshift-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/redshift-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/redshift-diffusion", 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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license: creativeml-openrail-m
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thumbnail: "https://huggingface.co/nitrosocke/redshift-diffusion/resolve/main/images/redshift-diffusion-samples-01s.jpg"
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tags:
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- stable-diffusion
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- text-to-image
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---
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### Redshift Diffusion
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language:
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- en
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license: creativeml-openrail-m
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thumbnail: "https://huggingface.co/nitrosocke/redshift-diffusion/resolve/main/images/redshift-diffusion-samples-01s.jpg"
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tags:
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- stable-diffusion
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- text-to-image
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- image-to-image
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---
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### Redshift Diffusion
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