Instructions to use sd-dreambooth-library/taras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sd-dreambooth-library/taras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sd-dreambooth-library/taras", 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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### taras on Stable Diffusion via Dreambooth
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#### model by kirilpok
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It can be used by modifying the `instance_prompt`: **photo of sks taras**
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You can also train your own concepts and upload them to the library by using [this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_training.ipynb).
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### taras on Stable Diffusion via Dreambooth
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#### model by kirilpok
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Stable Diffusion model fine-tuned with the Taras Shevchenko (Ukrainian poet, writer, artist, public and political figure, as well as folklorist and ethnographer.) concept taught to Stable Diffusion with Dreambooth.
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It can be used by modifying the `instance_prompt`: **photo of sks taras**
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You can also train your own concepts and upload them to the library by using [this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_training.ipynb).
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