update path

.idea/Multidimensional_Multilevel_Bias_Detection.iml

@@ -4,7 +4,7 @@
     <content url="file://$MODULE_DIR$">
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="jdk" jdkName="Python 3.9 (venv) (15)" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.9 (Stereotype_Detection)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>

.idea/misc.xml

@@ -1,4 +1,4 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (venv) (15)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (Stereotype_Detection)" project-jdk-type="Python SDK" />
 </project>

README.md

@@ -1,5 +1,5 @@
 ---
-title: Multidimensional_Multilevel_Bias_Detection
+title: Stereotype_Detection
 emoji: 📉
 colorFrom: blue
 colorTo: yellow

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
-from bias_detector import Detector
+from stereotype_detector import Detector
 
-st.title("Multidimensional Multilevel Stereotype Detection")
+st.title("Stereotype Detection")
 
 EXAMPLES = {
     "Gender": "The baby loved the presence of his caring mommy.",
@@ -34,11 +34,10 @@ def format_results(results, bias_level):
     return formatted
 
 level = st.selectbox("Select the Detection Levels:", ("Sentence","Token"))
-dimension = st.selectbox("Select the Stereotype Dimensions:", ("All","Gender","Religion","Race","Profession"))
 
 if st.button("Load Models"):
     with st.spinner('Loading models...'):
-        st.session_state["detector"] = Detector(level, dimension)
+        st.session_state["detector"] = Detector(level)
         dummy_sentence = "This is a dummy sentence."
         dummy_result = st.session_state["detector"].predict([dummy_sentence])
         if dummy_result:

bias_detector/__init__.py

@@ -1 +0,0 @@
-from .bias_detector import Detector

stereotype_detector/__init__.py

@@ -0,0 +1 @@
+from .stereotype_detector import Detector

bias_detector/bias_detector.py → stereotype_detector/stereotype_detector.py

@@ -7,41 +7,25 @@ class Detector:
     A class for detecting various forms of bias in text using pre-trained models.
     """
 
-    def __init__(self, classifier, model_type):
+    def __init__(self, classifier):
         """
         Initializes the detector with a specific model.
 
         Args:
             classifier (str): The type of classifier to use.
-            model_type (str): The type of the model to use.
         """
         self.classifier = classifier
-        self.model_type = model_type
         self.classifier_model_mapping = {
-                "Token": {
-                    "All": "wu981526092/Token-Level-Multidimensional-Bias-Detector",
-                    "Race": "wu981526092/Token-Level-Race-Bias-Detector",
-                    "Gender": "wu981526092/Token-Level-Gender-Bias-Detector",
-                    "Profession": "wu981526092/Token-Level-Profession-Bias-Detector",
-                    "Religion": "wu981526092/Token-Level-Religion-Bias-Detector",
-                },
-                "Sentence": {
-                    "All": "wu981526092/Sentence-Level-Multidimensional-Bias-Detector",
-                    "Religion": "wu981526092/Sentence-Level-Religion-Bias-Detector",
-                    "Profession": "wu981526092/Sentence-Level-Profession-Bias-Detector",
-                    "Race": "wu981526092/Sentence-Level-Race-Bias-Detector",
-                    "Gender": "wu981526092/Sentence-Level-Gender-Bias-Detector",
-                }
+                "Token": "wu981526092/Token-Level-Stereotype-Detector",
+                "Sentence": "wu981526092/Sentence-Level-Stereotype-Detector"
         }
 
         if classifier not in self.classifier_model_mapping:
             raise ValueError(f"Invalid classifier. Expected one of: {list(self.classifier_model_mapping.keys())}")
 
-        if model_type not in self.classifier_model_mapping[classifier]:
-            raise ValueError(
-                f"Invalid model_type for {classifier}. Expected one of: {list(self.classifier_model_mapping[classifier].keys())}")
 
-        self.model_path = self.classifier_model_mapping[classifier][model_type]
+
+        self.model_path = self.classifier_model_mapping[classifier]
         API_token = os.getenv("BIAS_DETECTOR_API_KEY")
         # Using pipeline for inference
         if classifier == 'Token':
@@ -80,7 +64,7 @@ class Detector:
 
 
 if __name__ == '__main__':
-    detector_test = Detector("Sentence","Gender")
+    detector_test = Detector("Sentence")
     test_data = ["The girl performed poorly at reading in school.","Sir is an address showing respect for a person. It usually refers to a male."]
     result = detector_test.predict(test_data)
     print(result)