Instructions to use TheAwakenOne/camberganng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheAwakenOne/camberganng 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("TheAwakenOne/camberganng") prompt = "CMBER a 1960'S Ford Mustang with camber suspension, parked for a photoshoot" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example
#6
by TheAwakenOne - opened
- README.md +5 -0
- images/example_hokeneqxd.png +0 -0
README.md
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@@ -40,6 +40,11 @@ widget:
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street in the rain
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output:
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url: images/example_f34uxrllw.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: CMBER
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license: other
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street in the rain
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output:
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url: images/example_f34uxrllw.png
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- text: >-
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CMBER a black Toyota crown with camber suspension, in an elegant garage with
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neon lights, a very far shot,
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output:
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url: images/example_hokeneqxd.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: CMBER
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license: other
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images/example_hokeneqxd.png
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