rearrange layout for blog post

app.py

@@ -82,6 +82,7 @@ with demo:
                     gpu_selector = gpu_selector_fn(["3090", "T4", "T4 *2", "A100 (80GB)"])
                 with gr.Column():
                     omit_offload = omit_offload_fn()
+
             # Show plot when the gradio app is initialized
             plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
             gr.Markdown(
@@ -106,26 +107,28 @@ with demo:
         with gr.TabItem("OPT: Summ"):
             plot_fn = functools.partial(get_plot, "OPT: Summarization")
             with gr.Row():
-                with gr.Column(scale=0.3, min_width=200):
+                with gr.Column():
                     gpu_selector = gpu_selector_fn(["3090", "T4", "T4 *2", "A100 (80GB)"])
+                with gr.Column():
                     omit_offload = omit_offload_fn()
-                    gr.Markdown(
-                        """
-                        ### Assistant Model
-                        - `facebook/opt-125m`
-
-                        ### Model Names:
-                        - 1.3B: `facebook/opt-1.3b`
-                        - 6.7B: `facebook/opt-6.7b`
-                        - 30B: `facebook/opt-30b`
-                        - 66B: `facebook/opt-66b`
-
-                        ### Dataset used as input prompt:
-                        - CNN Dailymail (3.0.0, validation set)
-                        """
-                    )
-                # Show plot when the gradio app is initialized
-                plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
+
+            # Show plot when the gradio app is initialized
+            plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
+            gr.Markdown(
+                """
+                ### Assistant Model
+                - `facebook/opt-125m`
+
+                ### Model Names:
+                - 1.3B: `facebook/opt-1.3b`
+                - 6.7B: `facebook/opt-6.7b`
+                - 30B: `facebook/opt-30b`
+                - 66B: `facebook/opt-66b`
+
+                ### Dataset used as input prompt:
+                - CNN Dailymail (3.0.0, validation set)
+                """
+            )
             # Update plot when any of the inputs change
             plot_inputs = [gpu_selector, omit_offload]
             gpu_selector.change(fn=plot_fn, inputs=plot_inputs, outputs=plot)
@@ -133,23 +136,28 @@ with demo:
         with gr.TabItem("Whisper: ARS"):
             plot_fn = functools.partial(get_plot, "Whisper: ARS")
             with gr.Row():
-                with gr.Column(scale=0.3, min_width=200):
+                with gr.Column():
                     gpu_selector = gpu_selector_fn(["3090", "T4"])
+                with gr.Column():
                     omit_offload = omit_offload_fn()
-                    gr.Markdown(
-                        """
-                        ### Assistant Model
-                        - `openai/whisper-tiny`
-
-                        ### Model Names:
-                        - large-v2: `openai/whisper-large-v2`
-
-                        ### Dataset used as input prompt:
-                        - Librispeech ARS (clean, validation set)
-                        """
-                    )
-                # Show plot when the gradio app is initialized
-                plot = gr.Image(value=plot_fn("T4", "No"))
+
+            # Show plot when the gradio app is initialized
+            plot = gr.Image(value=plot_fn("T4", "No"))
+            gr.Markdown(
+                """
+                ### Assistant Model
+                - `openai/whisper-tiny`
+
+                ### Model Names:
+                - large-v2: `openai/whisper-large-v2`
+
+                ### Dataset used as input prompt:
+                - Librispeech ARS (clean, validation set)
+
+
+
+                """
+            )
             # Update plot when any of the inputs change
             plot_inputs = [gpu_selector, omit_offload]
             gpu_selector.change(fn=plot_fn, inputs=plot_inputs, outputs=plot)
@@ -157,25 +165,27 @@ with demo:
         with gr.TabItem("CodeGen: Code"):
             plot_fn = functools.partial(get_plot, "CodeGen: Code Generation")
             with gr.Row():
-                with gr.Column(scale=0.3, min_width=200):
+                with gr.Column():
                     gpu_selector = gpu_selector_fn(["3090", "T4", "T4 *2", "A100 (80GB)"])
+                with gr.Column():
                     omit_offload = omit_offload_fn()
-                    gr.Markdown(
-                        """
-                        ### Assistant Model
-                        - `Salesforce/codegen-350M-mono`
-
-                        ### Model Names:
-                        - 2B: `Salesforce/codegen-2B-mono`
-                        - 6B: `Salesforce/codegen-6B-mono`
-                        - 16B: `Salesforce/codegen-16B-mono`
-
-                        ### Dataset used as input prompt:
-                        - The Stack (python)
-                        """
-                    )
-                # Show plot when the gradio app is initialized
-                plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
+            # Show plot when the gradio app is initialized
+            plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
+            gr.Markdown(
+                """
+                ### Assistant Model
+                - `Salesforce/codegen-350M-mono`
+
+                ### Model Names:
+                - 2B: `Salesforce/codegen-2B-mono`
+                - 6B: `Salesforce/codegen-6B-mono`
+                - 16B: `Salesforce/codegen-16B-mono`
+
+                ### Dataset used as input prompt:
+                - The Stack (python)
+
+                """
+            )
             # Update plot when any of the inputs change
             plot_inputs = [gpu_selector, omit_offload]
             gpu_selector.change(fn=plot_fn, inputs=plot_inputs, outputs=plot)
@@ -183,26 +193,28 @@ with demo:
         with gr.TabItem("Flan-T5: Summ"):
             plot_fn = functools.partial(get_plot, "Flan-T5: Summarization")
             with gr.Row():
-                with gr.Column(scale=0.3, min_width=200):
+                with gr.Column():
                     gpu_selector = gpu_selector_fn(["3090", "T4", "T4 *2", "A100 (80GB)"])
+                with gr.Column():
                     omit_offload = omit_offload_fn()
-                    gr.Markdown(
-                        """
-                        ### Assistant Model
-                        - `google/flan-t5-small`
-
-                        ### Model Names:
-                        - large: `google/flan-t5-large`
-                        - xl: `google/flan-t5-xl`
-                        - xxl: `google/flan-t5-xxl`
-                        - ul2: `google/flan-ul2`
-
-                        ### Dataset used as input prompt:
-                        - CNN Dailymail (3.0.0, validation set)
-                        """
-                    )
-                # Show plot when the gradio app is initialized
-                plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
+
+            # Show plot when the gradio app is initialized
+            plot = gr.Image(value=plot_fn("A100 (80GB)", "No"))
+            gr.Markdown(
+                """
+                ### Assistant Model
+                - `google/flan-t5-small`
+
+                ### Model Names:
+                - large: `google/flan-t5-large`
+                - xl: `google/flan-t5-xl`
+                - xxl: `google/flan-t5-xxl`
+                - ul2: `google/flan-ul2`
+
+                ### Dataset used as input prompt:
+                - CNN Dailymail (3.0.0, validation set)
+                """
+            )
             # Update plot when any of the inputs change
             plot_inputs = [gpu_selector, omit_offload]
             gpu_selector.change(fn=plot_fn, inputs=plot_inputs, outputs=plot)