Instructions to use cocktailpeanut/optimus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cocktailpeanut/optimus 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("cocktailpeanut/optimus") prompt = "optimus is cleaning the house with broomstick" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add generated example
#7
by clem HF Staff - opened
- README.md +5 -0
- images/example_r4qqskt3c.png +0 -0
README.md
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@@ -37,6 +37,11 @@ widget:
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- text: optimus is in a japanese manga page
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output:
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url: images/example_dcyajrq9j.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: optimus
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license: other
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- text: optimus is in a japanese manga page
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output:
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url: images/example_dcyajrq9j.png
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- text: >-
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optimus is sun tanning on a beach under an umbrella in miami. Next to him
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there's a man in a bathing suit sun bathing too
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output:
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url: images/example_r4qqskt3c.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: optimus
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license: other
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images/example_r4qqskt3c.png
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