Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_name = "Qwen/Qwen2.5-Coder-14B-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, load_in_4bit=True, device_map="auto")
+
+def chat(message, history):
+    messages = [{"role": "user", "content": message}]
+    text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer(text, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7)
+    response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
+    history.append((message, response))
+    return history, ""
+
+demo = gr.ChatInterface(chat)
+demo.launch()