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app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
+from threading import Thread
+
+model_id = "AuriLab/gpt-bi"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+def generar_texto(prompt):
+    streamer = TextIteratorStreamer(tokenizer, skip_prompt=True)
+    
+    inputs = tokenizer(prompt, return_tensors="pt")
+    
+    thread = Thread(target=model.generate, kwargs={
+        "input_ids": inputs.input_ids,
+        "max_new_tokens": 50,
+        "streamer": streamer,
+        "do_sample": True
+    })
+    thread.start()
+    
+    output = prompt
+    yield output
+    
+    for new_token in streamer:
+        output += new_token
+        yield output
+
+textbox = gr.Textbox(
+    lines=5,
+    placeholder="Escribe tu prompt aquí...",
+    label="Generación en tiempo real"
+)
+
+
+interfaz = gr.Interface(
+    fn=generar_texto,
+    inputs=textbox,
+    outputs=textbox,
+    title="Generador de Texto con Streamer",
+    description="Escribe y los tokens aparecerán en tiempo real en la misma caja"
+)
+
+if __name__ == "__main__":
+    interfaz.launch()