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import tempfile ,os | |
import gradio as gr | |
from transformers import VitsModel, AutoTokenizer,pipeline | |
import torch | |
import numpy as np | |
import torchaudio | |
model = VitsModel.from_pretrained("SeyedAli/Persian-Speech-synthesis") | |
tokenizer = AutoTokenizer.from_pretrained("SeyedAli/Persian-Speech-synthesis") | |
def TTS(text): | |
inputs = tokenizer(text, return_tensors="pt") | |
with torch.no_grad(): | |
output = model(**inputs).waveform | |
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp: | |
torchaudio.save(fp, output, model.config.sampling_rate) | |
return fp.name | |
iface = gr.Interface(fn=TTS, inputs="text", outputs="audio") | |
iface.launch(share=False) |