hi

app.py

@@ -1,7 +1,7 @@
 import json
 import pandas as pd
 import gradio as gr
-from transformers import PreTrainedTokenizerFast, BertForMaskedLM
+# from transformers import PreTrainedTokenizerFast, BertForMaskedLM
 from datasets import load_dataset
 import infer
 
@@ -68,13 +68,15 @@ with gr.Blocks() as demo:
         gr.Markdown("Enter a DNA sequence and the coordinates at which its sample was taken to get a genus prediction. Click 'I'm feeling lucky' to see a prediction for a random sequence.")
 
         # Collect inputs for app (DNA and location)
-        with gr.Column():
-            inp_dna = gr.Textbox(label="DNA", placeholder="e.g. AACAATGTA... (min 200 and max 660 characters)")
-        with gr.Column():
-            with gr.Row():
-                inp_lat = gr.Textbox(label="Latitude", placeholder="e.g. -3.009083")    
-            with gr.Row():
-                inp_lng = gr.Textbox(label="Longitude", placeholder="e.g. -58.68281")
+        with gr.row():
+            with gr.Column():
+                inp_dna = gr.Textbox(label="DNA", placeholder="e.g. AACAATGTA... (min 200 and max 660 characters)")
+
+            with gr.Column():
+                with gr.Row():
+                    inp_lat = gr.Textbox(label="Latitude", placeholder="e.g. -3.009083")    
+                with gr.Row():
+                    inp_lng = gr.Textbox(label="Longitude", placeholder="e.g. -58.68281")
 
         with gr.Row():
             btn_run = gr.Button("Run")
@@ -91,11 +93,13 @@ with gr.Blocks() as demo:
     
     with gr.Tab('DNA Embedding Space Similarity Visualizer'):
         gr.Markdown("If the highest genus probability is very low for your DNA sequence, we can still examine the DNA embedding of the sequence in relation to known samples for clues.")
-        with gr.Column():
-            gr.Markdown("Plot of your DNA sequence among other known species clusters.")
+        
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown("Plot of your DNA sequence among other known species clusters.")
 
-        with gr.Column():
-            gr.Markdown("Plot of the five most common species at your sample coordinate.")
+            with gr.Column():
+                gr.Markdown("Plot of the five most common species at your sample coordinate.")