Update intro

app.py

@@ -91,7 +91,7 @@ with gr.Blocks() as demo:
 
         Target-Driven Distillation (TDD) is a state-of-the-art consistency distillation model that largely accelerates the inference processes of diffusion models. Using its delicate strategies of *target timestep selection* and *decoupled guidance*, models distilled by TDD can generated highly detailed images with only a few steps.
 
-        Besides, TDD is also available for distilling video generation models. This space presents the TDD-distilled version of [SVD-xt 1.1](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt-1-1).
+        Besides, TDD is also available for distilling video generation models. This space presents TDD-distilled [SVD-xt 1.1](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt-1-1).
 
         [**Project Page**](https://redaigc.github.io/TDD/) **|** [**Paper**](https://arxiv.org/abs/2409.01347) **|** [**Code**](https://github.com/RedAIGC/Target-Driven-Distillation) **|** [**Model**](https://huggingface.co/RED-AIGC/TDD) **|** [🤗 **TDD-SDXL Demo**](https://huggingface.co/spaces/RED-AIGC/TDD) **|** [🤗 **TDD-SVD Demo**](https://huggingface.co/spaces/RED-AIGC/SVD-TDD)