How to use bytedance-research/OneReward 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("bytedance-research/OneReward", dtype=torch.bfloat16, device_map="cuda") 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]
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{ "peft_type": "LORA", "base_model_name_or_path": "black-forest-labs/FLUX.1-Fill-dev", "revision": null, "task_type": "UNDEFINED", "lora_alpha": 1, "r": null, "lora_dropout": 0.0, "bias": "none", "target_modules": [ "transformer" ] }
