Upload folder using huggingface_hub

app.py

@@ -4,6 +4,7 @@ from huggingface_hub import hf_hub_download
 import joblib
 
 # Download and load the model
+
 model_path = hf_hub_download(repo_id="rakeshambudkar/machine_failure_model", filename="best_machine_failure_model_v1.joblib")
 # model_path = hf_hub_download(repo_id="praneeth232/machine_failure_model", filename="best_machine_failure_model_v1.joblib")
 model = joblib.load(model_path)
@@ -25,11 +26,11 @@ tool_wear = st.number_input("Tool Wear (min)", min_value=0, max_value=300, value
 
 # Assemble input into DataFrame
 input_data = pd.DataFrame([{
-    'Air temperature': air_temp,
-    'Process temperature': process_temp,
-    'Rotational speed': rot_speed,
+    'Air_temperature': air_temp,
+    'Process_temperature': process_temp,
+    'Rotational_speed': rot_speed,
     'Torque': torque,
-    'Tool wear': tool_wear,
+    'Tool_wear': tool_wear,
     'Type': Type
 }])
 

requirements.txt

@@ -4,3 +4,4 @@ streamlit==1.43.2
 joblib==1.5.1
 scikit-learn==1.6.0
 xgboost==2.1.4
+mlflow==3.0.1