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--- |
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base_model: stabilityai/stable-diffusion-3.5-medium |
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library_name: peft |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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This model is trained using Flow-GRPO with LoRA. We provide only the LoRA weights here, so you will need to download the SD 3.5 Medium base model first. |
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## Model Details |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** https://github.com/yifan123/flow_grpo |
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- **Paper:** https://www.arxiv.org/pdf/2505.05470 |
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## Uses |
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```python |
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import torch |
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from diffusers import StableDiffusion3Pipeline |
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from diffusers.schedulers import FlowMatchEulerDiscreteScheduler |
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from peft import PeftModel |
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model_id = "stabilityai/stable-diffusion-3.5-medium" |
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lora_ckpt_path = "jieliu/SD3.5M-FlowGRPO-PickScore" |
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device = "cuda" |
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pipe = StableDiffusion3Pipeline.from_pretrained(model_id, torch_dtype=torch.float16) |
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pipe.transformer = PeftModel.from_pretrained(pipe.transformer, lora_ckpt_path) |
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pipe.transformer = pipe.transformer.merge_and_unload() |
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pipe = pipe.to(device) |
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prompt = 'a jung male cyborg with white hair sitting down on a throne in a dystopian world, digital art, epic' |
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image = pipe(prompt, height=512, width=512, num_inference_steps=40,guidance_scale=4.5).images[0] |
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image.save("flow_grpo_pickscore.png") |
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``` |
