Change title

apps/mlm.py

@@ -26,7 +26,7 @@ def load_model(masked_text, model_name):
 
 
 def app():
-    st.header("RoBERTa Hindi")
+    st.title("RoBERTa Hindi")
     st.markdown("This demo uses multiple hindi transformer models for Masked Language Modelling (MLM).")
 
     models_list = list(cfg["models"].keys())
@@ -44,14 +44,6 @@ def app():
 
     results_df = pd.DataFrame(columns=["Model Name", "Filled Token", "Filled Text"])
 
-    st.sidebar.markdown(
-        "### Models\n"
-        "- [RoBERTa Hindi](https://huggingface.co/flax-community/roberta-hindi)\n"
-        "- [Indic Transformers Hindi](https://huggingface.co/neuralspace-reverie/indic-transformers-hi-bert)\n"
-        "- [HindiBERTa](https://huggingface.co/mrm8488/HindiBERTa)\n"
-        "- [RoBERTa Hindi Guj San](https://huggingface.co/surajp/RoBERTa-hindi-guj-san)"
-    )
-
     model_names = []
     filled_masked_texts = []
     filled_tokens = []
@@ -63,6 +55,14 @@ def app():
         select_text = st.sidebar.selectbox("Select any of the following text", texts)
         masked_text = st.text_area("Please type a masked sentence to fill", select_text)
 
+    st.sidebar.markdown(
+        "### Models\n"
+        "- [RoBERTa Hindi](https://huggingface.co/flax-community/roberta-hindi)\n"
+        "- [Indic Transformers Hindi](https://huggingface.co/neuralspace-reverie/indic-transformers-hi-bert)\n"
+        "- [HindiBERTa](https://huggingface.co/mrm8488/HindiBERTa)\n"
+        "- [RoBERTa Hindi Guj San](https://huggingface.co/surajp/RoBERTa-hindi-guj-san)"
+    )
+
     # pd.set_option('max_colwidth',30)
     if st.button("Fill the Mask!"):
         with st.spinner("Filling the Mask..."):