Instructions to use finegrain/finegrain-product-placement-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use finegrain/finegrain-product-placement-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("finegrain/finegrain-product-placement-lora") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things

- Xet hash:
- 7a47c617168e0d3d4e7f4814625a290e18c8dceeaf132b0635bb44d2acd13c93
- Size of remote file:
- 2.24 MB
- SHA256:
- ce631766414b43115d05235a03687c05cd3fac221854c7a4ad2520d479c952d7
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