Update app.py

app.py

@@ -3,6 +3,7 @@ import os
 import pandas as pd
 
 path_to_generation_model = str(os.environ['path_to_generation_model'])
+path_to_GNER_model       = str(os.environ['path_to_GNER_model'])
 
 path_to_L_model = str(os.environ['path_to_L_model'])
 path_to_S_model = str(os.environ['path_to_S_model'])
@@ -40,6 +41,10 @@ description_G = """
 A t5 model tuned to performer text-generation, and predict emotion as well as the character experiencing those emotions.
 """
 
+description_GNER = """
+A t5 model tuned to performer text-generation, and predict which characters are present in the report.
+"""
+
 example_main = ["en", "it", "pl"]
 
 examples = [
@@ -87,7 +92,15 @@ interface_model_G = gr.Interface.load(
             api_key=read_token_ii,
 )
 
+interface_model_NER = gr.Interface.load(
+            name=path_to_GNER_model,
+            description=description_GNER,
+            examples=examples_g,
+            title="NER Generation",
+            api_key=read_token_ii,
+)
+
 gr.TabbedInterface(
-    [interface_words, interface_model_L, interface_model_S, interface_model_G], 
-    ["Intro", "Large Multilingual", "Base En", "En Generation"]
+    [interface_words, interface_model_L, interface_model_S, interface_model_G, interface_model_NER], 
+    ["Intro", "SA Large Multilingual", "SA Base En", "SA En Generation", "NER Generation"]
 ).launch()