fixes to elem_classes

app.py

@@ -102,7 +102,7 @@ def sample_predict(image,truth_labels=None):
     return {LABELS[i]: float(probabilities[i]) for i in range(len(LABELS))}
 
 custom_css = """
-.gradio-container img {
+.tab img{
     object-fit: fill !important;
     width: 100% !important;
     height: 100% !important;
@@ -110,10 +110,10 @@ custom_css = """
 }
 """
 
-with gradio.Blocks() as demo:
+with gradio.Blocks(css=custom_css) as demo:
     gradio.Markdown("# PathMNIST Image Classification")
 
-    with gradio.Tab("Predict",css=custom_css):
+    with gradio.Tab("Predict", elem_classes="tab"):
         gradio.Markdown("## Upload a tissue image for classification")
         with gradio.Row():
             input_img = gradio.Image(height=512, width=512)
@@ -122,7 +122,7 @@ with gradio.Blocks() as demo:
                 btn = gradio.Button("Predict")
                 btn.click(fn=predict, inputs=input_img, outputs=output_lbl)
 
-    with gradio.Tab("Examples (Validation)",css=custom_css):
+    with gradio.Tab("Examples (Validation)", elem_classes="tab"):
         gradio.Markdown("## Select an example below to test the model against the PathMNIST validation dataset")
         
         with gradio.Row():
@@ -139,7 +139,7 @@ with gradio.Blocks() as demo:
             cache_examples=True,
         )
 
-    with gradio.Tab("Examples (Test)",css=custom_css):
+    with gradio.Tab("Examples (Test)", elem_classes="tab"):
         gradio.Markdown("## Select an example below to test the model against the PathMNIST test dataset")
         
         with gradio.Row():