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Update finetune_xtts_hf.py
Browse files- finetune_xtts_hf.py +22 -2
finetune_xtts_hf.py
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import os
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import subprocess
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from huggingface_hub import HfApi, HfFolder
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# === Configuración ===
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HF_TOKEN = os.environ.get("HF_TOKEN") #
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HF_REPO_ID = "sob111/xttsv2-es-finetuned" #
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OUTPUT_PATH = "./output_model"
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CONFIG_PATH = "./config.json"
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print("=== Guardando token de Hugging Face ===")
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HfFolder.save_token(HF_TOKEN)
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# === Iniciar entrenamiento XTTSv2 ===
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print("=== Iniciando entrenamiento XTTSv2 ===")
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try:
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print(f"✅ Fine-tuning completado y subido a {HF_REPO_ID}")
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import os
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import subprocess
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from huggingface_hub import HfApi, HfFolder
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from datasets import load_dataset
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# === Configuración ===
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HF_TOKEN = os.environ.get("HF_TOKEN") # define en los Secrets del Space
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HF_REPO_ID = "sob111/xttsv2-es-finetuned" # tu repo de destino
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OUTPUT_PATH = "./output_model"
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CONFIG_PATH = "./config.json"
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print("=== Guardando token de Hugging Face ===")
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HfFolder.save_token(HF_TOKEN)
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# === Descargar dataset desde Hugging Face ===
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print("=== Descargando dataset sob111/voxpopuli_es_500 ===")
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ds = load_dataset("sob111/voxpopuli_es_500", split="train", token=HF_TOKEN)
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# Guardar metadata.json en el formato esperado por Coqui TTS
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os.makedirs("./voxpopuli_es_500", exist_ok=True)
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meta_file = "./voxpopuli_es_500/metadata.json"
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with open(meta_file, "w", encoding="utf-8") as f:
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for sample in ds:
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f.write(
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f'{{"audio_file": "{sample["audio_file"]}", '
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f'"text": "{sample["text"]}", '
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f'"speaker_name": "{sample.get("speaker_name", "speaker")}"}}
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'
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)
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print(f"✅ Metadata guardada en {meta_file}")
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# === Iniciar entrenamiento XTTSv2 ===
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print("=== Iniciando entrenamiento XTTSv2 ===")
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try:
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)
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print(f"✅ Fine-tuning completado y subido a {HF_REPO_ID}")
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