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 (#5)
Browse files- Add generated example (4771cb679a3cc977329d67cba8ca67bd26095b08)
- README.md +3 -0
- images/example_hetrfzm5n.png +0 -0
README.md
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@@ -31,6 +31,9 @@ widget:
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- text: optimus is chilling on a yacht with many bikini ladies on his side
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output:
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url: images/example_uf13dj16i.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 chilling on a yacht with many bikini ladies on his side
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output:
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url: images/example_uf13dj16i.png
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- text: optimus has angel wings and flies around in new york city
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output:
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url: images/example_hetrfzm5n.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_hetrfzm5n.png
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