Create app.py

app.py

@@ -0,0 +1,18 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+MODEL_ID = "Qwen/Qwen2.5-Coder-1.5B-Instruct"  # or your model
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype=torch.float16 if device=="cuda" else torch.float32)
+model.to(device)
+
+def generate(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)
+    outputs = model.generate(**inputs, max_new_tokens=256, do_sample=True, temperature=0.2)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+demo = gr.Interface(fn=generate, inputs="text", outputs="text")
+demo.launch()