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
- Draw Things
- DiffusionBee
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README.md
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- **Developed by:** Deci
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- **Model type:** Diffusion-based text-to-image generation model
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- **Language(s) (NLP):** English
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- **License:** The model is released under the [CreativeML Open RAIL++-M
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### Model Resources
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- **Blog:** [A technical overview](https://deci.ai/blog/decidiffusion-2-0-text-to-image-generation-optimized-for-cost-effective-hardware/)
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- **Developed by:** Deci
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- **Model type:** Diffusion-based text-to-image generation model
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- **Language(s) (NLP):** English
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- **License:** The model is released under the [CreativeML Open RAIL++-M](https://huggingface.co/Deci/DeciDiffusion-v1-0/blob/main/LICENSE-WEIGHTS.md) license.
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### Model Resources
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- **Blog:** [A technical overview](https://deci.ai/blog/decidiffusion-2-0-text-to-image-generation-optimized-for-cost-effective-hardware/)
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