--- license: apache-2.0 datasets: - yuvalkirstain/pickapic_v2 language: - en pipeline_tag: text-to-image --- **Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation** (https://huggingface.co/papers/2402.10210) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/657be24e8d360b690d5b665f/uzhoFO22ZdQ5XjBxxDA1a.png) # SPIN-Diffusion-iter3 This model is a self-play fine-tuned diffusion model at iteration 3 from [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) using synthetic data based on the winner images of the [yuvalkirstain/pickapic_v2](https://huggingface.co/datasets/yuvalkirstain/pickapic_v2) dataset. We have also made a Gradio Demo at [UCLA-AGI/SPIN-Diffusion-demo-v1](https://huggingface.co/spaces/UCLA-AGI/SPIN-Diffusion-demo-v1). ## Model Details ### Model Description - Model type: A diffusion model with unet fine-tuned, based on the structure of stable diffusion 1.5 - Language(s) (NLP): Primarily English - License: Apache-2.0 - Finetuned from model: runwayml/stable-diffusion-v1-5 ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2.0e-05 - train_batch_size: 8 - distributed_type: multi-GPU - num_devices: 8 - train_gradient_accumulation_steps: 32 - total_train_batch_size: 2048 - optimizer: AdamW - lr_scheduler: "linear" - lr_warmup_steps: 200 - num_training_steps: 500 ### Usage To use the model, you must first load the SD1.5 base model and then substitute its unet with our fine-tuned version. ```python from diffusers import StableDiffusionPipeline, UNet2DConditionModel import torch model_id = "runwayml/stable-diffusion-v1-5" pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) unet_id = "UCLA-AGI/SPIN-Diffusion-iter3" unet = UNet2DConditionModel.from_pretrained(unet_id, subfolder="unet", torch_dtype=torch.float16) pipe.unet = unet ###The rest of your generation code ``` ### Evaluation Results on [Pick-a-pic test set](https://huggingface.co/datasets/yuvalkirstain/pickapic_v2/viewer/default/test_unique) | Metric | Best of Five | Mean | Median |-----------------------|---------------------------|--------|------- | HPS | 0.28 | 0.27 | 0.27 | Aesthetic | 6.26 | 5.94 | 5.98 | Image Reward | 1.13 | 0.53 | 0.67 | Pickapic Score | 22.00 |21.36 | 21.46 ## Citation ``` @misc{yuan2024self, title={Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation}, author={Yuan, Huizhuo and Chen, Zixiang and Ji, Kaixuan and Gu, Quanquan}, year={2024}, eprint={2402.10210}, archivePrefix={arXiv}, primaryClass={cs.LG} } ```