Instructions to use prithivMLmods/Flux-Product-Ad-Backdrop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/Flux-Product-Ad-Backdrop 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("prithivMLmods/Flux-Product-Ad-Backdrop") prompt = "Product Ad, Captured at eye-level, a close-up shot captures a pile of fried chicken wings in a white paper cup. The chicken wings are a vibrant brown color, adding a pop of color to the scene. The cup is placed on a light brown wooden table, creating a stark contrast with the vibrant blue sky in the background. To the right of the chicken wings, a slice of lemon, a red onion, and a red radish are placed on the table. The radish, and red onions are arranged in a circular pattern, adding depth to the composition. The backdrop is blurred, suggesting a fair day." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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base_model = "black-forest-labs/FLUX.1-dev"
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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lora_repo = "
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trigger_word = "Product Ad"
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pipe.load_lora_weights(lora_repo)
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base_model = "black-forest-labs/FLUX.1-dev"
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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lora_repo = "prithivMLmods/Flux-Product-Ad-Backdrop"
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trigger_word = "Product Ad"
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pipe.load_lora_weights(lora_repo)
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