Create app.py

app.py

@@ -0,0 +1,51 @@
+from transformers import AutoTokenizer
+from transformers import pipeline
+from transformers import TextDataset, DataCollatorForLanguageModeling
+from transformers import Trainer, TrainingArguments,AutoModelWithLMHead
+
+chef = pipeline('text-generation', model="./models/en_gpt2-medium_rachel_replics", tokenizer=model_type)
+tmp = chef(f"<s>NOTFRIEND: Do you like Ross?\nRACHEL:")[0]['generated_text']
+tmp = tmp[tmp.find(f"RACHEL: ") + len("RACHEL") + 2 : tmp.find('</s>')]
+tmp
+
+# gradio part 
+def echo(message, history, model):
+    
+    chef = pipeline('text-generation', model="./models/en_gpt2-medium_rachel_replics", tokenizer=model_type)
+    
+    if model=="gpt2-medium":
+        answer = chef(f"<s>NOTFRIEND: {message}}\nRACHEL:")[0]['generated_text']
+        answer = tmp[tmp.find(f"RACHEL: ") + len("RACHEL") + 2 : tmp.find('</s>')]
+        return answer
+    
+    elif model=="gpt2-medium":
+        answer = chef(f"<s>NOTFRIEND: {message}}\nRACHEL:")[0]['generated_text']
+        answer = tmp[tmp.find(f"RACHEL: ") + len("RACHEL") + 2 : tmp.find('</s>')]
+        return answer
+    
+    elif model=="gpt2-medium":
+        answer = chef(f"<s>NOTFRIEND: {message}}\nRACHEL:")[0]['generated_text']
+        answer = tmp[tmp.find(f"RACHEL: ") + len("RACHEL") + 2 : tmp.find('</s>')]
+        return answer
+    
+
+
+
+title = "Chatbot who speaks like Rachel from Friends"
+description = "You have a good opportunity to have a dialog with actress from Friends - Rachel Green"
+
+model = gr.Dropdown(["gpt2", "gpt2-medium", "gpt2-large"], label="LLM", info="What model do you want to use?", value="gpt2-medium")
+
+with gr.Blocks() as demo:
+
+    gr.ChatInterface(
+        fn=echo,
+        title=title,
+        description=description,
+        additional_inputs=[model],
+        retry_btn=None,
+        undo_btn=None,
+        clear_btn=None,
+    )
+
+demo.launch(debug=False, share=True)