import os import gradio as gr os.system("pip install kantts -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html") os.system("pip install numpy==1.22.0") from modelscope.models.audio.tts import SambertHifigan from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks import IPython.display as ipd model_dir = os.path.abspath("./pretrain_work_dir") custom_infer_abs = { 'voice_name': 'F7', 'am_ckpt': os.path.join(model_dir, 'tmp_am', 'ckpt'), 'am_config': os.path.join(model_dir, 'tmp_am', 'config.yaml'), 'voc_ckpt': os.path.join(model_dir, 'orig_model', 'basemodel_16k', 'hifigan', 'ckpt'), 'voc_config': os.path.join(model_dir, 'orig_model', 'basemodel_16k', 'hifigan', 'config.yaml'), 'audio_config': os.path.join(model_dir, 'data', 'audio_config.yaml'), 'se_file': os.path.join(model_dir, 'data', 'se', 'se.npy') } kwargs = {'custom_ckpt': custom_infer_abs} model_id = SambertHifigan(os.path.join(model_dir, "orig_model"), **kwargs) inference = pipeline(task=Tasks.text_to_speech, model=model_id) def infer(text): output = inference(input=text) with open("myfile.wav", mode='bx') as f: f.write(output["output_wav"]) return "myfile.wav" app = gr.Blocks() with app: gr.HTML("