Delete app.py

app.py

@@ -1,44 +0,0 @@
-import gradio as gr
-import re
-import time
-import streamlit as st
-from transformers import pipeline, Conversation, AutoTokenizer
-#"meta-llama/Llama-2-13b-chat-hf"
-my_config = {'model_name': "BramVanroy/Llama-2-13b-chat-dutch", 'do_sample': True, 'temperature': 0.1, 'repetition_penalty': 1.1, 'max_new_tokens': 500}
-
-print(f"Loading the model: {my_config['model_name']}....")
-time_load_model_start = time.time()
-
-print(time_load_model_start)
-
-# Load the model and tokenizer outside of the functions
-llm = pipeline("text-generation",
-                model=my_config['model_name'],
-                tokenizer=AutoTokenizer.from_pretrained(my_config['model_name']),
-                do_sample=my_config['do_sample'],
-                temperature=my_config['temperature'],
-                repetition_penalty=my_config['repetition_penalty'],
-                max_new_tokens=my_config['max_new_tokens']
-              )
-time_load_model_end = time.time()
-elapsed_time = time_load_model_end - time_load_model_start
-print(f"Elapsed time to load the model: {elapsed_time:.2f} sec")
-
-def get_answer(chatbot, input_text):
-    start_time = time.time()
-    print(f"Processing the input\n {input_text}\n")
-    print('Processing the answer....')
-    conversation = Conversation(input_text)
-    print(f"Conversation(input_text): {conversation}")
-    output = (chatbot(conversation))[1]['content']
-    elapsed_time = time.time() - start_time
-    #Add the last print statement to the output variable
-    output += f"\nAnswered in {elapsed_time:.1f} seconds, Nr generated words: {count_words(output)}"
-    
-    return output
-
-
-
-#gr.ChatInterface(get_answer(llm, text)).launch()
-demo = gr.Interface(fn=get_answer, inputs="text", outputs="text")
-demo.launch()