Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+model_name = "anasmkh/customized_llama3.1_8b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype=torch.float16)
+
+generator = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_new_tokens=64,
+    temperature=1.5,
+    min_p=0.1
+)
+
+def generate_response(prompt):
+  messages = [
+    {"role": "user", "content": prompt},
+  ]
+  response = generator(messages)[0]['generated_text']
+  return response.split("<|end_header_id|>")[1].strip()
+
+demo = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(lines=5, label="Enter your prompt"),
+    outputs=gr.Textbox(label="Model Response")
+)
+
+demo.launch()