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 (#4)
Browse files- Add generated example (17f5fc60f9330a81a9347178c4721e080316a620)
- README.md +6 -0
- images/example_ptslpz22u.png +0 -0
README.md
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@@ -18,6 +18,12 @@ widget:
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- text: tutu cat running in field of green grass in backyard
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output:
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url: images/example_opabycwas.png
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---
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"Tutu, the most graceful and elegant of female nebelung cats."
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- text: tutu cat running in field of green grass in backyard
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output:
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url: images/example_opabycwas.png
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- text: >-
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Tutu cat, perched on a windowsill, gazing thoughtfully at the city skyline
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at dusk, with the vibrant hues of sunset reflecting in its bright
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yellow-green eyes
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output:
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url: images/example_ptslpz22u.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_ptslpz22u.png
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