Instructions to use aipicasso/commonart-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aipicasso/commonart-beta with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aipicasso/commonart-beta", 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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This is a text-to-image model learning from CC-BY-4.0, CC-0 or CC-0 like images.
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## Updates
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- 2024/09/25: Update the model. (for paper)
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- 2024/09/21: Update the model. (30000 L4 GPU hours)
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- 2024/09/09: Release this model. (20000 L4 GPU hours)
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This is a text-to-image model learning from CC-BY-4.0, CC-0 or CC-0 like images.
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## Updates
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- 2024/10/22: Release the [paper](https://jxiv.jst.go.jp/index.php/jxiv/preprint/view/936)
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- 2024/09/25: Update the model. (for paper)
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- 2024/09/21: Update the model. (30000 L4 GPU hours)
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- 2024/09/09: Release this model. (20000 L4 GPU hours)
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