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| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| import gradio as gr | |
| tokenizer = AutoTokenizer.from_pretrained("PlanTL-GOB-ES/gpt2-base-bne") | |
| model = AutoModelForCausalLM.from_pretrained("PlanTL-GOB-ES/gpt2-base-bne") | |
| def text_generation(input_text, seed): | |
| input_ids = tokenizer(input_text, return_tensors="pt").input_ids | |
| torch.manual_seed(seed) # Max value: 18446744073709551615 | |
| outputs = model.generate(input_ids, do_sample=True, min_length=35, max_length=100) | |
| generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True) | |
| return generated_text | |
| title = "Demo Generador de Texto Espa帽ol GPT2" | |
| description = "Aplicaci贸n para generar texto por ecarbo" | |
| gr.Interface( | |
| text_generation, | |
| [gr.inputs.Textbox(lines=2, label="Ingrese el texto"), gr.inputs.Number(default=10, label="Ingrese numero semilla")], | |
| [gr.outputs.Textbox(type="auto", label="Texto Generado")], | |
| title=title, | |
| description=description, | |
| theme="huggingface" | |
| ).launch() |