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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# DeciDiffusion 2.0
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DeciDiffusion 2.0 is a 732 million parameter text-to-image latent diffusion model generated with the help of AutoNAC, Deci's proprietary Neural Architecture Search technology. Advanced training techniques were used to speed up training, improve training performance, and achieve better inference quality.
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## Model Details
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# DeciDiffusion 2.0
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DeciDiffusion 2.0 is a 732 million parameter text-to-image latent diffusion model, generated with the help of AutoNAC, Deci's proprietary Neural Architecture Search technology. Advanced training techniques were used to speed up training, improve training performance, and achieve better inference quality.
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## Model Details
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