improve gradio blocks interface

app.py

@@ -54,9 +54,6 @@ You can reset the interface anytime by clicking the **Reset** button.
 - **📸Object Detection**: Identify and label objects within the image.
 - **📸✍🏻OCR**: Extract text from the image.
 - **📸Region Proposal**: Detect key regions in the image for detailed captioning.
-
-### Join us : 
-🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/qdfnvSPcqP) On 🤗Huggingface:[MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Build Tonic](https://git.tonic-ai.com/contribute)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
 """
 
 model_presentation = f"""
@@ -80,6 +77,9 @@ In addition to text tasks, 🙏🏻PLeIAs/📸📈✍🏻Florence-PDF also incor
 
 """
 
+joinus = """🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/qdfnvSPcqP) On 🤗Huggingface:[MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Build Tonic](https://git.tonic-ai.com/contribute)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
+"""
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
@@ -216,6 +216,9 @@ with gr.Blocks(title="Tonic's 🙏🏻PLeIAs/📸📈✍🏻Florence-PDF") as if
             with gr.Column(scale=1):
                 with gr.Group():
                     gr.Markdown(description)
+        with gr.Row():
+            with gr.Accordion("Join Us", open=True):
+                gr.Markdown(joinus)
         with gr.Row():
             with gr.Column(scale=1):
                 image_input = gr.Image(type="pil", label="Input Image")