Instructions to use bochen2079/tutu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bochen2079/tutu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bochen2079/tutu") prompt = "tutu cat sitting in car" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example (#10)
Browse files- Add generated example (03428cc74e827b74795fb38a30b8a47302b70c40)
- README.md +6 -0
- images/example_019zeukco.png +0 -0
README.md
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@@ -54,6 +54,12 @@ widget:
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in the background
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output:
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url: images/example_fyas36zun.png
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---
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"Tutu, the most graceful and elegant of female nebelung cats."
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in the background
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output:
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url: images/example_fyas36zun.png
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- text: >-
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Tutu cat, with sparkling fairy wings, fluttering around a magical garden
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filled with vibrant flowers, where every petal glows softly under the gentle
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moonlight, hyperrealistic, 4k, DSLR photography
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output:
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url: images/example_019zeukco.png
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---
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"Tutu, the most graceful and elegant of female nebelung cats."
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images/example_019zeukco.png
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