Updated inference.py

apps/inference.py

@@ -40,35 +40,6 @@ def app():
 
     texts = target_text_df["text"]
 
-    st.markdown("""## Select any of the following text : """)
-    masked_text = st.selectbox("", texts)
-
-    st.write("You selected:", masked_text)
-
-    selected_models = st.multiselect(
-        "Choose models",
-        [
-            "flax-community/roberta-hindi",
-            "mrm8488/HindiBERTa",
-            "neuralspace-reverie/indic-transformers-hi-bert",
-            "surajp/RoBERTa-hindi-guj-san",
-        ],
-        ["flax-community/roberta-hindi"],
-    )
-
-    models_list = list(cfg["models"].keys())
-
-        models = st.multiselect(
-        "Choose models",
-        models_list,
-        models_list[0],
-    )
-
-    target_text_path = "./mlm_custom/mlm_targeted_text.csv"
-    target_text_df = pd.read_csv(target_text_path)
-
-    texts = target_text_df["text"]
-
     st.sidebar.title("Hindi MLM")
 
     pick_random = st.sidebar.checkbox("Pick any random text")
@@ -92,7 +63,9 @@ def app():
 
             for selected_model in models:
 
-                filled_sentence, filled_token = load_model(masked_text, cfg["models"][selected_model])
+                filled_sentence, filled_token = load_model(
+                    masked_text, cfg["models"][selected_model]
+                )
                 model_names.append(selected_model)
                 filled_tokens.append(filled_token)
                 filled_masked_texts.append(filled_sentence)
@@ -102,24 +75,3 @@ def app():
             results_df["Filled Text"] = filled_masked_texts
 
             st.table(results_df)
-
-
-
-    if st.button("Fill the Mask!"):
-        with st.spinner("Filling the Mask..."):
-            models = []
-            predicted_tokens = []
-            predicted_sentence = []
-            for i in range(len(selected_models)):
-                filled_sentence = load_model(masked_text, selected_models[i])
-                # st.write(filled_sentence)
-                models.append(selected_models[i])
-                predicted_tokens.append(filled_sentence[0]["token_str"])
-                predicted_sentence.append(filled_sentence[0]["sequence"])
-
-            results_df = pd.DataFrame()
-            results_df["Model Name"] = models
-            results_df["Predicted Word"] = predicted_tokens
-            results_df["Sentence"] = predicted_sentence
-            st.dataframe(results_df)
-