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 (#1)
Browse files- Add generated example (723d67c1e6bfe9d8fb2cd036204add1a9df28aeb)
- README.md +5 -3
- images/example_qcf7xcq03.png +0 -0
README.md
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---
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base_model: black-forest-labs/FLUX.1-dev
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license: apache-2.0
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tags:
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- text-to-image
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- flux
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- lora
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- diffusers
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- template:sd-lora
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---
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"Tutu, the most graceful and elegant of female nebelung cats."
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---
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base_model: black-forest-labs/FLUX.1-dev
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license: apache-2.0
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tags:
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- text-to-image
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- flux
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- lora
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- diffusers
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- template:sd-lora
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instance_prompt: tutu cat
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widget:
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- text: tutu cat sitting in car
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output:
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url: images/example_qcf7xcq03.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_qcf7xcq03.png
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