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license: cc-by-nc-sa-4.0 |
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# Enhancing Diffusion Models with Text-Encoder Reinforcement Learning |
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Official PyTorch codes for paper [Enhancing Diffusion Models with Text-Encoder Reinforcement Learning](https://arxiv.org/abs/2311.15657) |
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## Results on SDXL-Turbo |
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We also applied our method to the recent model [sdxl-turbo](https://huggingface.co/stabilityai/sdxl-turbo). The model is trained with [ImageReward](https://github.com/THUDM/ImageReward) feedback through direct back-propagation to save training time. Test with the following codes |
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``` |
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## Note: sdturbo requires latest diffusers installed from source with the following command |
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git clone https://github.com/huggingface/diffusers |
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cd diffusers |
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pip install -e . |
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``` |
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``` |
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from diffusers import AutoPipelineForText2Image |
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import torch |
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pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16") |
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pipe = pipe.to("cuda") |
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pipe.load_lora_weights('chaofengc/sdxl-turbo_texforce') |
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pt = ['a photo of a cat.'] |
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img = pipe(prompt=pt, num_inference_steps=1, guidance_scale=0.0).images[0] |
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``` |
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