add our trained model

app.py

@@ -2,6 +2,18 @@ import gradio as gr
 from openai import OpenAI
 import os
 
+from transformers import pipeline
+# from dotenv import load_dotenv, find_dotenv
+import huggingface_hub
+
+
+
+# _ = load_dotenv(find_dotenv()) # read local .env file
+hf_token= os.environ['HF_TOKEN']
+huggingface_hub.login(hf_token)
+
+pipe = pipeline("token-classification", model="elshehawy/finer-ord-transformers", use_auth_token=True)
+
 
 llm_model = 'gpt-3.5-turbo-0125'
 # openai.api_key = os.environ['OPENAI_API_KEY']
@@ -20,7 +32,7 @@ def get_completion(prompt, model=llm_model):
     )
     return response.choices[0].message.content
 
-def find_orgs(sentence):
+def find_orgs(sentence, choice):
     prompt = f"""
     Find all organizations in the text delimited by triple backticks.
     
@@ -30,13 +42,17 @@ def find_orgs(sentence):
     ```
     You should always start your answer with "Organizations are: "
     """
-    return get_completion(prompt)
+    if choice='GPT':
+        return get_completion(prompt)
+    else:
+        return pipe(sentence)
+
 
 example = """
 My latest exclusive for The Hill : Conservative frustration over Republican efforts to force a House vote on reauthorizing the Export - Import Bank boiled over Wednesday during a contentious GOP meeting.
 """
-
+radio_btn = gr.Radio(choices=['GPT', 'iSemantics'], value='iSemantics')
 textbox = gr.Textbox(label="Enter your text", placeholder="", lines=4)
 
-iface = gr.Interface(fn=find_orgs, inputs=textbox, outputs="text",  examples=[[example]])
-iface.launch(share=True)
+iface = gr.Interface(fn=find_orgs, inputs=[textbox, radio_btn], outputs="text",  examples=[[example]])
+iface.launch(share=True)