app.py

"""from transformers import AutoModelForCausalLM, AutoTokenizer
import os

model = AutoModelForCausalLM.from_pretrained(
 "Qwen/CodeQwen1.5-7B-Chat",
 torch_dtype="auto",
 device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("Qwen/CodeQwen1.5-7B-Chat")

messages = [
 {"role": "system", "content": "You are a helpful assistant."},
]
import gradio as gr

def greet(prompt):
 messages.append({"role": "user", "content": prompt})
 text = tokenizer.apply_chat_template(
 messages,
 tokenize=False,
 add_generation_prompt=True
 )
 model_inputs = tokenizer([text], return_tensors="pt")

 generated_ids = model.generate(
 model_inputs.input_ids,
 max_new_tokens=512
 )
 generated_ids = [
 output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
 ]

 response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0].text
 
 messages.append({"role": "bot", "content": response})

 return response

demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch(share=True)"""

import gradio as gr

gr.load("models/Qwen/CodeQwen1.5-7B-Chat").launch(share=True)