add deployed model

.idea/workspace.xml

@@ -6,6 +6,7 @@
   <component name="ChangeListManager">
     <list default="true" id="e2eb7b8e-f942-4b21-8057-83c784e0946e" name="Changes" comment="">
       <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/README.md" beforeDir="false" afterPath="$PROJECT_DIR$/README.md" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/app.py" beforeDir="false" afterPath="$PROJECT_DIR$/app.py" afterDir="false" />
     </list>
     <option name="SHOW_DIALOG" value="false" />

README.md

@@ -8,6 +8,7 @@ sdk_version: 4.23.0
 app_file: app.py
 pinned: false
 python_version: 3.9
+model: [Proddis/pbc_complication_model]
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -8,10 +8,14 @@ from matplotlib import pyplot as plt
 from utils.data_processor import DataProcessor
 from utils.model_predictor import ModelPredictor
 from utils.data import patients_data, key_to_display_name_and_value_conversion
+from huggingface_hub import hf_hub_download
+import joblib
 
+model = joblib.load(
+	hf_hub_download("Proddis/pbc_complication_model", "RandomForestClassifier_trained_pipeline.joblib")
+)
 
 
-model = gr.load("models/Proddis/pbc_complication_model").launch()
 categorical_names = joblib.load('resources/categorical_names.pkl')
 target_labels = joblib.load('resources/target_labels.pkl')
 selected_features = []