Instructions to use den123/squidgame with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use den123/squidgame 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("den123/squidgame") prompt = "Angelina Jolie wearing green tracksuit" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example (#2)
Browse files- Add generated example (23ad3e70169fba52538dad9ce1ff25853040f077)
- README.md +3 -0
- images/example_vn56fwu82.png +3 -0
README.md
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@@ -8,6 +8,9 @@ widget:
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- text: Angelina Jolie wearing green tracksuit
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output:
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url: images/example_hzhiqrcwv.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: squidgame
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license: apache-2.0
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- text: Angelina Jolie wearing green tracksuit
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output:
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url: images/example_hzhiqrcwv.png
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- text: TAylor Swift wearing green tracksuit, number"69"
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output:
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url: images/example_vn56fwu82.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: squidgame
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license: apache-2.0
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images/example_vn56fwu82.png
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Git LFS Details
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