Update details

apps/classifier.py

@@ -18,27 +18,28 @@ def load_model(input_text, model_name_or_path):
 
 
 def app():
-    st.title("Marathi News Classifier")
+    st.title("मराठी Marathi News Classifier")
 
     st.markdown(
         "This demo uses the below fine-tuned models for marathi news classification:\n"
         "- [IndicNLP Marathi News Classifier](https://huggingface.co/flax-community/mr-indicnlp-classifier) fine-tuned on "
-        "[IndicNLP Marathi News Dataset](https://github.com/ai4bharat/indicnlp_corpus#indicnlp-news-article-classification-dataset)"
-        "\n"
+        "[IndicNLP Marathi News Dataset](https://github.com/ai4bharat/indicnlp_corpus#indicnlp-news-article-classification-dataset)\n\n"
+        "> `IndicNLP` model predicts one of these 3 classes - `['lifestyle', 'entertainment', 'sports']`"
+        "\n\n"
         "- [iNLTK Marathi News Classifier](https://huggingface.co/flax-community/mr-inltk-classifier) fine-tuned on "
-        "[Marathi News Dataset](https://www.kaggle.com/disisbig/marathi-news-dataset)"
+        "[Marathi News Dataset](https://www.kaggle.com/disisbig/marathi-news-dataset)\n\n"
+        "> `iNLTK` model predicts one of these 3 classes - `['state', 'entertainment', 'sports']`"
     )
 
-    st.markdown("`IndicNLP Marathi News Dataset` consists of 3 classes - `['lifestyle', 'entertainment', 'sports']`")
-    st.markdown("`iNLTK Marathi News Dataset` consists of 3 classes - `['state', 'entertainment', 'sports']`")
-
     st.markdown(
-        "Can't figure out where to get a sample text other than the predefined ones? Visit any of the following links, "
-        "copy any headline and see if the model is predicting the respective class or not.\n"
+        "❓ Can't figure out where to get a sample text other than the predefined ones? ❓\n\n We have provided "
+        "Marathi newspaper links (section wise) below. Head over to any section of your choice, "
+        "copy any headline and paste below to see if the model is predicting the respective class correctly or not?\n"
         "- [entertainment](https://maharashtratimes.com/entertainment/articlelist/19359255.cms)\n"
         "- [sports](https://maharashtratimes.com/sports/articlelist/2429056.cms)\n"
         "- [lifestyle](https://maharashtratimes.com/lifestyle-news/articlelist/2429025.cms)\n"
-        "- [state](https://maharashtratimes.com/maharashtra/articlelist/2429066.cms)"
+        "- [state](https://maharashtratimes.com/maharashtra/articlelist/2429066.cms)\n\n"
+        "> 📒 NOTE: Both models are not trained on above headlines! Feel free to use any headline from any newspaper"
     )
 
     classifier = st.sidebar.selectbox("Select a Model", index=0, options=["IndicNLP", "iNLTK"])
@@ -56,8 +57,8 @@ def app():
     )
 
     sample_texts = [
-        "अध्यक्ष शरद पवार आणि उपमुख्यमंत्री अजित पवार यांची भेट घेतली.",
-        "मोठी बातमी! उद्या दुपारी १ वाजता जाहीर होणार दहावीचा निकाल",
+        "रोहित शर्माने सरावाला सुरुवात करण्यापूर्वी भारतीय खेळाडूला दिला कानमंत्र, म्हणाला...",
+        "जॉनी लीवर यांनी नम्रता संभेरावला दिलं खास गिफ्ट, अभिनेत्रीने व्यक्त केल्या भावना",
         "Custom",
     ]
     model_name_or_path = cfg["models"][classifier]
@@ -73,5 +74,5 @@ def app():
         with st.spinner("Generating prediction..."):
             result = load_model(text_to_classify, model_name_or_path)
 
-            st.markdown("**Predicted label:** " + result[0]["label"])
-            st.markdown("**Score:** " + str(round(result[0]["score"], 2)))
+            st.markdown(f"**Predicted label:** {result[0]["label"]}")
+            st.markdown(f"**Score:** {round(result[0]["score"], 2)}")

apps/mlm.py

@@ -19,7 +19,7 @@ def load_model(input_text, model_name_or_path):
 
 
 def app():
-    st.title("RoBERTa Marathi")
+    st.title("RoBERTa Marathi - मराठी भाषा")
 
     st.markdown(
         "This demo uses [RoBERTa for Marathi](https://huggingface.co/flax-community/roberta-base-mr) model "
@@ -27,13 +27,15 @@ def app():
     )
 
     st.markdown(
-        "Can't figure out where to get a sample text other than the predefined ones? Visit this "
-        "[link](https://maharashtratimes.com/entertainment/articlelist/19359255.cms), copy any headline and mask a word."
+        "❓Can't figure out where to get a sample text other than the predefined ones?❓\n\n"
+        "Use any custom sentence with masked word or copy any headline from [link](https://maharashtratimes.com/entertainment/articlelist/19359255.cms), and mask a word.\n"
+        "> 📒 NOTE: Supports only single `<mask>` word"
     )
 
     masked_texts = [
         "मोठी बातमी! उद्या दुपारी <mask> वाजता जाहीर होणार दहावीचा निकाल",
-        "अध्यक्ष <mask> पवार आणि उपमुख्यमंत्री अजित पवार यांची भेट घेतली.",
+        "जॉनी लीवर यांनी नम्रता संभेरावला दिलं <mask> गिफ्ट, अभिनेत्रीने व्यक्त केल्या भावना"
+        # "अध्यक्ष <mask> पवार आणि उपमुख्यमंत्री अजित पवार यांची भेट घेतली.",
     ]
 
     input_text = st.sidebar.selectbox("Select a Text", options=masked_texts)