Update app.py

app.py

@@ -81,6 +81,7 @@ with gr.Blocks(css=".gradio-container {background-color: #b0cda8};") as demo:
       <h3 style="text-align: left;"> This is a demo of Animal Pose ControlNet, which is a model trained on runwayml/stable-diffusion-v1-5 with a new type of conditioning.</h3>  
       <h3 style="text-align: left;"> While this is definitely a work in progress, you can still try it out by using the p5 sketch to create a keypoint image and using it as the conditioning image.</h3>
       <h3 style="text-align: left;"> The model was generated as part of the Hugging Face Jax Diffusers sprint.  Thank you to both Hugging Face and Google Cloud who provided the TPUs for training!
+      <h3 style="text-align: left;"> The dataset was build using the OpenPifPaf Animalpose plugin.</h3>
       </h3>
       """) 
   with gr.Row():
@@ -98,11 +99,12 @@ with gr.Blocks(css=".gradio-container {background-color: #b0cda8};") as demo:
             )
       gr.Markdown(
         """
-        <h3 style="text-align: left;"> The dataset was build using the [OpenPifPaf Animalpose plugin](https://openpifpaf.github.io/plugins_animalpose.html).</h3>
-        [Dataset](https://huggingface.co/datasets/JFoz/dog-poses-controlnet-dataset)  
-        [Diffusers model](https://huggingface.co/JFoz/dog-pose)  
+        [OpenPifPaf Animalpose](https://openpifpaf.github.io/plugins_animalpose.html).
+        [Dataset](https://huggingface.co/datasets/JFoz/dog-cat-pose)  
+        [Diffusers model](https://huggingface.co/JFoz/dog-cat-pose)  
         [WANDB Training Report](https://wandb.ai/john-fozard/dog-cat-pose/runs/kmwcvae5)
-        [Github](https://github.com/fi4cr/animalpose)   
+        [Training Scripts](https://github.com/fi4cr/animalpose/tree/main/scripts) 
+        [p5.js](https://p5js.org)
         """)     
 
   run_btn.click(fn=infer, inputs = [prompts, negative_prompts, conditioning_image], outputs = output)