updated layout

app.py

@@ -56,13 +56,13 @@ def start_app():
         )
         gr.HTML(f"""<div class="app-header"><img src="{logo_data_url}" alt="AlpineLLM" style="max-height:10%; width: auto; margin: 10px auto; display: block;"></div>""")
         gr.HTML("""<div class="quick-links"><a href="https://github.com/Borzyszkowski/AlpineLLM" target="_blank">GitHub</a> | <a href="https://huggingface.co/Borzyszkowski/AlpineLLM-Tiny-10M-Base" target="_blank">Model Page</a></div>""")
-        gr.HTML("""<div class="notice"><strong>Heads up:</strong> This space shows a free CPU-only demo of the model, so inference may take a few seconds. Text generation of the tiny model may lack full coherence due to its limited size and character-level tokenization. For improved results, consider using the source repository to load larger pretrained weights and run inference on a GPU. </div>""")
+        gr.HTML("""<div class="notice"><strong>Heads up:</strong> This space shows a free CPU-only demo of the model, so inference may take a few seconds. Text generation of the tiny model may lack full coherence due to its limited size and character-level tokenization. Consider using the source repository to load larger pretrained weights and run inference on a GPU. </div> <br> """)
         
         gr.Markdown("<h4> About AlpineLLM</h4>")
         gr.Markdown(
             "<p>"
             "AlpineLLM-Tiny-10M-Base is a lightweight base language model with ~10.8 million trainable parameters. It was pre-trained from scratch on raw text corpora drawn primarily from public-domain literature on alpinism, including expedition narratives and climbing essays. <br><br>"
-            "This demo showcases the model’s text generation capabilities within its specialized domain. Please note that AlpineLLM is a base model, and it has not been fine-tuned for downstream tasks such as summarization or dialogue. Its outputs reflect patterns learned directly from the training texts. <br><br>"
+            "This demo showcases the model's text generation capabilities within its specialized domain. Please note that AlpineLLM is a base model, and it has not been fine-tuned for downstream tasks such as summarization or dialogue. Its outputs reflect patterns learned directly from the training texts. <br><br>"
             "</p>"
         )
         with gr.Row():

style.py

@@ -7,6 +7,7 @@ body, .gradio-container { font-family: "Noto Sans SC", "Microsoft YaHei", "PingF
 .gradio-container { padding: 4px 0 !important; max-width: 1200px !important; margin: 0 auto !important; }
 .gradio-container [data-testid="tabs"], .gradio-container .tabs { margin-top: 0 !important; }
 .gradio-container [data-testid="tabitem"], .gradio-container .tabitem { padding-top: 4px !important; }
+.gradio-container .wrap { gap: 0 !important; }
 .quick-links { text-align: center; padding: 8px 0; border: 1px solid #e5e7eb; border-radius: 8px; margin: 8px auto; max-width: 1200px; }
 .quick-links a { margin: 0 12px; font-size: 14px; font-weight: 600; color: #3b82f6; text-decoration: none; }
 .quick-links a:hover { text-decoration: underline; }