import gradio as gr from transformers import AutoModelForCausalLM, AutoTokenizer import torch # Cargar modelo Qwen2.5 model_name = "Qwen/Qwen1.5-0.5B" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float32) # FunciĆ³n de respuesta def chat(message): inputs = tokenizer(message, return_tensors="pt") output = model.generate(**inputs, max_new_tokens=50) return tokenizer.decode(output[0], skip_special_tokens=True) # Interfaz Gradio iface = gr.Interface(fn=chat, inputs="text", outputs="text", title="Chat con Qwen2.5") iface.launch()