Update README.md

README.md

@@ -9,7 +9,7 @@ tags:
 ---
 
 # Hyper-SD
-Official Repository of the paper: *[Hyper-SD]()*. (already submitted, coming very soon!)
+Official Repository of the paper: *[Hyper-SD](https://arxiv.org/abs/2404.13686)*.
 
 Project Page: https://hyper-sd.github.io/
 
@@ -105,7 +105,7 @@ Take the 2-steps LoRA as an example, you can also use other LoRAs for the corres
 import torch
 from diffusers import DiffusionPipeline, DDIMScheduler
 from huggingface_hub import hf_hub_download
-base_model_id = "stabilityai/stable-diffusion-v1-5"
+base_model_id = "runwayml/stable-diffusion-v1-5"
 repo_name = "ByteDance/Hyper-SD"
 # Take 2-steps lora as an example
 ckpt_name = "Hyper-SD15-2steps-lora.safetensors"
@@ -126,7 +126,7 @@ You can flexibly adjust the number of inference steps and eta value to achieve b
 import torch
 from diffusers import DiffusionPipeline, TCDScheduler
 from huggingface_hub import hf_hub_download
-base_model_id = "stabilityai/stable-diffusion-v1-5"
+base_model_id = "runwayml/stable-diffusion-v1-5"
 repo_name = "ByteDance/Hyper-SD"
 ckpt_name = "Hyper-SD15-1step-lora.safetensors"
 # Load model.
@@ -311,5 +311,12 @@ image.save('image_out.png')
 
 ## Citation
 ```bibtex
-
+@misc{ren2024hypersd,
+      title={Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis}, 
+      author={Yuxi Ren and Xin Xia and Yanzuo Lu and Jiacheng Zhang and Jie Wu and Pan Xie and Xing Wang and Xuefeng Xiao},
+      year={2024},
+      eprint={2404.13686},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
 ```