Update app.py

app.py

@@ -15,32 +15,33 @@ st.set_page_config(layout="wide")
 
 st.title("Demo for EIC NER")
 
-model_list = ['akdeniz27/bert-base-turkish-cased-ner',
-             'akdeniz27/convbert-base-turkish-cased-ner',
-             'akdeniz27/xlm-roberta-base-turkish-ner',
-             'xlm-roberta-large-finetuned-conll03-english']
+model_list = ['/arunavsk1/my-awesome-pubmed-bert/'
+             # 'akdeniz27/convbert-base-turkish-cased-ner',
+             # 'akdeniz27/xlm-roberta-base-turkish-ner',
+             # 'xlm-roberta-large-finetuned-conll03-english'
+             ]
 
-st.sidebar.header("Select NER Model")
-model_checkpoint = st.sidebar.radio("", model_list)
+# st.sidebar.header("Select NER Model")
+# model_checkpoint = st.sidebar.radio("", model_list)
 
-st.sidebar.write("For details of models: 'https://huggingface.co/akdeniz27/")
-st.sidebar.write("")
+# st.sidebar.write("For details of models: 'https://huggingface.co/akdeniz27/")
+# st.sidebar.write("")
 
-xlm_agg_strategy_info = "'aggregation_strategy' can be selected as 'simple' or 'none' for 'xlm-roberta' because of the RoBERTa model's tokenization approach."
+# xlm_agg_strategy_info = "'aggregation_strategy' can be selected as 'simple' or 'none' for 'xlm-roberta' because of the RoBERTa model's tokenization approach."
 
-st.sidebar.header("Select Aggregation Strategy Type")
-if model_checkpoint == "akdeniz27/xlm-roberta-base-turkish-ner":
-    aggregation = st.sidebar.radio("", ('simple', 'none'))
-    st.sidebar.write(xlm_agg_strategy_info)
-elif model_checkpoint == "xlm-roberta-large-finetuned-conll03-english":
-    aggregation = st.sidebar.radio("", ('simple', 'none'))
-    st.sidebar.write(xlm_agg_strategy_info)
-    st.sidebar.write("")
-    st.sidebar.write("This English NER model is included just to show the zero-shot transfer learning capability of XLM-Roberta.")
-else:
-    aggregation = st.sidebar.radio("", ('first', 'simple', 'average', 'max', 'none'))
+# st.sidebar.header("Select Aggregation Strategy Type")
+# if model_checkpoint == "akdeniz27/xlm-roberta-base-turkish-ner":
+#     aggregation = st.sidebar.radio("", ('simple', 'none'))
+#     st.sidebar.write(xlm_agg_strategy_info)
+# elif model_checkpoint == "xlm-roberta-large-finetuned-conll03-english":
+#     aggregation = st.sidebar.radio("", ('simple', 'none'))
+#     st.sidebar.write(xlm_agg_strategy_info)
+#     st.sidebar.write("")
+#     st.sidebar.write("This English NER model is included just to show the zero-shot transfer learning capability of XLM-Roberta.")
+# else:
+#     aggregation = st.sidebar.radio("", ('first', 'simple', 'average', 'max', 'none'))
     
-st.sidebar.write("Please refer 'https://huggingface.co/transformers/_modules/transformers/pipelines/token_classification.html' for entity grouping with aggregation_strategy parameter.")
+# st.sidebar.write("Please refer 'https://huggingface.co/transformers/_modules/transformers/pipelines/token_classification.html' for entity grouping with aggregation_strategy parameter.")
 
 st.subheader("Select Text Input Method")
 input_method = st.radio("", ('Select from Examples', 'Write or Paste New Text'))