try gpt-2

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from transformers import pipeline, AutoTokenizer
+from transformers import pipeline
 import os
 
 # Retrieve the Hugging Face API token from environment variables
@@ -11,16 +11,8 @@ if not hf_token:
 def authenticate_and_generate(message, history, system_message, max_tokens, temperature, top_p):
     try:
         # Initialize the text-generation pipeline with the provided token
-        text_generator = pipeline("text-generation", model="microsoft/Phi-3-mini-4k-instruct", use_auth_token=hf_token, trust_remote_code=True)
-        
-        # Load the tokenizer separately if needed
-        try:
-            tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct", use_auth_token=hf_token)
-        except Exception as e:
-            raise RuntimeError(f"Failed to load the tokenizer: {str(e)}")
-        
-        if text_generator.tokenizer is None:
-            raise RuntimeError("The tokenizer is not available. Check the model and API token.")
+        # Test with a known public model
+        text_generator = pipeline("text-generation", model="gpt2", use_auth_token=hf_token)
         
         # Ensure that system_message is a string
         system_message = str(system_message)
@@ -61,11 +53,4 @@ athena = gr.ChatInterface(
             """,
             label="System message"
         ),
-        gr.Slider(minimum=1, maximum=4096, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
-    ],
-)
-
-if __name__ == "__main__":
-    athena.launch()
+        gr.Slide