---
license: cc-by-nc-sa-4.0
---

# Enhancing Diffusion Models with Text-Encoder Reinforcement Learning

Official PyTorch codes for paper [Enhancing Diffusion Models with Text-Encoder Reinforcement Learning](https://arxiv.org/abs/2311.15657)

## Results on SDXL-Turbo

We also applied our method to the recent model [sdxl-turbo](https://huggingface.co/stabilityai/sdxl-turbo). The model is trained with [Q-Instruct](https://github.com/Q-Future/Q-Instruct) feedback through direct back-propagation to save training time. Test with the following codes

```
## Note: sdturbo requires latest diffusers installed from source with the following command
git clone https://github.com/huggingface/diffusers
cd diffusers
pip install -e .
```
```
from diffusers import AutoPipelineForText2Image
import torch

pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16")
pipe = pipe.to("cuda")
pipe.load_lora_weights('chaofengc/sdxl-turbo_texforce')

pt = ['a photo of a cat.']
img = pipe(prompt=pt, num_inference_steps=1, guidance_scale=0.0).images[0]
```

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6304798d41387c7f117558f7/MjIO6YL6RufTwmPTNIUBB.jpeg)