Update app.py

app.py

@@ -59,15 +59,15 @@ data.set_to_v1_vars()
 
 st.header('**Step 3:**  Load training and validation data')
 st.link_button("Go to Original Dataset", "https://huggingface.co/datasets/LEAP/subsampled_low_res/tree/main",use_container_width=True)
-st.code('''data.input_train = data.load_npy_file('train_input.npy')
-data.target_train = data.load_npy_file('train_target.npy')
-data.input_val = data.load_npy_file('val_input.npy')
-data.target_val = data.load_npy_file('val_target.npy')''',language='python')
+st.code('''data.input_train = data.load_npy_file('train_input_small.npy')
+data.target_train = data.load_npy_file('train_target_small.npy')
+data.input_val = data.load_npy_file('val_input_small.npy')
+data.target_val = data.load_npy_file('val_target_small.npy')''',language='python')
 
-data.input_train = data.load_npy_file('train_input.npy')
-data.target_train = data.load_npy_file('train_target.npy')
-data.input_val = data.load_npy_file('val_input.npy')
-data.target_val = data.load_npy_file('val_target.npy')
+data.input_train = data.load_npy_file('train_input_small.npy')
+data.target_train = data.load_npy_file('train_target_small.npy')
+data.input_val = data.load_npy_file('val_input_small.npy')
+data.target_val = data.load_npy_file('val_target_small.npy')
 
 
 
@@ -257,12 +257,12 @@ st.text('If you trained models with different hyperparameters, use the ones that
 st.header('**Step 6:**  Evaluate on scoring data')
 st.subheader('Do this at the VERY END (when you have finished tuned the hyperparameters for your model and are seeking a final evaluation)')
 st.subheader('Load scoring data')
-st.code('''data.input_scoring = np.load('scoring_input.npy')
-data.target_scoring = np.load('scoring_target.npy')
+st.code('''data.input_scoring = np.load('scoring_input_small.npy')
+data.target_scoring = np.load('scoring_target_small.npy')
 ''',language='python')
 
-data.input_scoring = np.load('scoring_input.npy')
-data.target_scoring = np.load('scoring_target.npy')
+data.input_scoring = np.load('scoring_input_small.npy')
+data.target_scoring = np.load('scoring_target_small.npy')