Instructions to use Deci/DeciDiffusion-v2-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Deci/DeciDiffusion-v2-0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Deci/DeciDiffusion-v2-0", 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 Settings
- Draw Things
- DiffusionBee
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- The autoencoding component of the model is lossy.
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### Bias
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The remarkable abilities of image-generation models can unintentionally amplify societal biases. DeciDiffusion was
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## How to Cite
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- The autoencoding component of the model is lossy.
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### Bias
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The remarkable abilities of image-generation models can unintentionally amplify societal biases. DeciDiffusion was trained with a focus on English descriptions. Consequently, non-English communities and cultures might be underrepresented, leading to a bias towards white and western norms. Outputs from non-English prompts are notably less accurate. Given these biases, users should approach DeciDiffusion with discretion, regardless of input.
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## How to Cite
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