added basic model comparison and ranking functionality

posts/model_exploration.py

@@ -1,22 +1,113 @@
 import streamlit as st
 
+# from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import pipeline
+
 title = "Model Exploration"
 description = "Comparison of hate speech detection models"
 date = "2022-01-26"
 thumbnail = "images/huggingface_logo.png"
 
+
+# Creates the forms for receiving multiple inputs to compare for a single 
+# model or one input to compare for two models
 def run_article():
-  st.markdown("""
-  # Making a Hate Speech Detection Model
+    st.markdown("""
+    # Making a Hate Speech Detection Model
+
+    This is where design choices will go.
+
+    # Model Output Ranking
+
+    For now, here's a link to the [space](https://huggingface.co/spaces/aymm/ModelOutputRankingTool).""")
+    with st.expander("Model Output Ranking Tool", expanded=False):     
+        with st.form(key='ranking'):
+            model_name = st.selectbox("Select a model to test",
+                   ["classla/roberta-base-frenk-hate",
+                    "cardiffnlp/twitter-roberta-base-hate",
+                    "Hate-speech-CNERG/dehatebert-mono-english"],
+                    )
+
+            input_1 = st.text_input("Input 1",
+                                    placeholder="We shouldn't let [IDENTITY] suffer.")
+            input_2 = st.text_input("Input 2",
+                                    placeholder="I'd rather die than date [IDENTITY].")
+            input_3 = st.text_input("Input 3",
+                                    placeholder="Good morning.")
+            inputs = [input_1, input_2, input_3]
 
-  This is where design choices will go.
+            if st.form_submit_button(label="Rank inputs"):
+                results = run_ranked(model_name, inputs)
+                st.dataframe(results)
+        
+      
+      
+    st.markdown("""
+    # Model Comparison
 
-  # Model Output Ranking Tool
+    For now, here's a link to the [space](https://huggingface.co/spaces/aymm/ModelComparisonTool).
+    """)
+    with st.expander("Model Comparison Tool", expanded=False): 
+        with st.form(key='comparison'):
+            model_name_1 = st.selectbox("Select a model to compare",
+                               ["cardiffnlp/twitter-roberta-base-hate",
+                                "Hate-speech-CNERG/dehatebert-mono-english",
+                                ],
+                                key='compare_model_1'
+                                )
+            model_name_2 = st.selectbox("Select another model to compare",
+                               ["cardiffnlp/twitter-roberta-base-hate",
+                                "Hate-speech-CNERG/dehatebert-mono-english",
+                                ],
+                                key='compare_model_2'
+                                )
+            input_text = st.text_input("Comparison input")
+            if st.form_submit_button(label="Compare models"):
+                results = run_compare(model_name_1, model_name_2, input_text)
+                st.dataframe(results)
+                
+        
+# Runs the received input strings through the given model and returns the 
+# output ranked by label and score (does not assume binary labels so the 
+# highest score for each label is at the top)
+def run_ranked(model, input_list):
+    classifier = pipeline("text-classification", model=model)
+    output = []
+    labels = {}
+    for inputx in input_list:
+        result = classifier(inputx)
+        curr = {}
+        curr['Input'] = inputx
+        label = result[0]['label']
+        curr['Label'] = label
+        score = result[0]['score']
+        curr['Score'] = score
+        if label in labels:
+            labels[label].append(curr)
+        else:
+            labels[label] = [curr]
+    for label in labels:
+        sort_list = sorted(labels[label], key=lambda item:item['Score'], reverse=True)
+        output += sort_list
+    return output
 
-  For now, here's a link to the [space](https://huggingface.co/spaces/aymm/ModelOutputRankingTool).
 
-  # Model Comparison Tool
+# Takes in two model names and returns the output of both models for that 
+# given input string
+def run_compare(name_1, name_2, text):
+    classifier_1 = pipeline("text-classification", model=name_1)
+    result_1 = classifier_1(text)
+    out_1 = {}
+    out_1['Model'] = name_1
+    out_1['Label'] = result_1[0]['label']
+    out_1['Score'] = result_1[0]['score']
+    classifier_2 = pipeline("text-classification", model=name_2)
+    result_2 = classifier_2(text)
+    out_2 = {}
+    out_2['Model'] = name_2
+    out_2['Label'] = result_2[0]['label']
+    out_2['Score'] = result_2[0]['score']
+    return [out_1, out_2]
+    
 
-  For now, here's a link to the [space](https://huggingface.co/spaces/aymm/ModelComparisonTool).
-  """)
-  
+