Update README.md

README.md

@@ -14,7 +14,7 @@ inference: False
 Flash Diffusion is a diffusion distillation method proposed in [Flash Diffusion: Accelerating Any Conditional
 Diffusion Model for Few Steps Image Generation](http://arxiv.org/abs/2406.02347) *by Clément Chadebec, Onur Tasar, Eyal Benaroche, and Benjamin Aubin.*
 This model is a **26.4M** LoRA distilled version of [SD1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) model that is able to generate images in **2-4 steps**. The main purpose of this model is to reproduce the main results of the paper.
-See our [live demo](https://huggingface.co/spaces/jasperai/FlashPixart).
+See our [live demo](https://huggingface.co/spaces/jasperai/FlashPixart) and [official implentation](https://github.com/gojasper/flash-diffusion).
 
 
 <p align="center">
@@ -65,6 +65,19 @@ The model was trained for 20k iterations on 2 H100 GPUs (representing approx. a
   - FID-30k: 12.41 (4 NFE)
   - FID-30k: 12.27 (2 NFE)
 
+## Citation
+If you find this work useful or use it in your research, please consider citing us
+
+```bibtex
+@misc{chadebec2024flash,
+      title={Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation}, 
+      author={Clement Chadebec and Onur Tasar and Eyal Benaroche and Benjamin Aubin},
+      year={2024},
+      eprint={2406.02347},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```
 
 ## License
 This model is released under the the Creative Commons BY-NC license.