hi

app.py

@@ -5,8 +5,6 @@ from transformers import PreTrainedTokenizerFast, BertForMaskedLM
 from datasets import load_dataset
 import infer
 
-embeddings_train = load_dataset("LofiAmazon/BOLD-Embeddings-Ecolayers-Amazon", split='train').to_pandas()
-
 with open("default_inputs.json", "r") as default_inputs_file:
     DEFAULT_INPUTS = json.load(default_inputs_file)
 
@@ -70,11 +68,13 @@ 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.Row():
+        with gr.Column():
             inp_dna = gr.Textbox(label="DNA", placeholder="e.g. AACAATGTA... (min 200 and max 660 characters)")
-        with gr.Row():
-            inp_lat = gr.Textbox(label="Latitude", placeholder="e.g. -3.009083")
-            inp_lng = gr.Textbox(label="Longitude", placeholder="e.g. -58.68281")
+        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")
@@ -85,7 +85,7 @@ with gr.Blocks() as demo:
         with gr.Row():
             gr.Markdown('Make plot or table for Top 5 species')
 
-        with gr.Column():
+        with gr.Row():
             genus_out = gr.Dataframe(headers=["DNA Only Pred Genus", "DNA Only Prob", "DNA & Env Pred Genus", "DNA & Env Prob"])
             btn_run.click(fn=predict_genus, inputs=[inp_dna, inp_lat, inp_lng], outputs=genus_out)