Pengwei Li
commited on
Commit
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8d99114
1
Parent(s):
3d50426
Update app.py
Browse files
app.py
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@@ -3,76 +3,26 @@ os.system("pip install gradio==2.8.0b2")
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import gradio as gr
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import numpy as np
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title = "
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description = "Gradio Demo for fairseq S2S: speech-to-speech translation models. To use it, simply add your audio, or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/
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examples = [
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["common_voice_es_en.flac","
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["common_voice_ru_18945535.flac","xm_transformer_600m-ru_en-multi_domain"],
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["common_voice_fr_19731305.mp3","xm_transformer_600m-fr_en-multi_domain"],
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["common_voice_en_ru.mp3","xm_transformer_600m-en_ru-multi_domain"],
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["common_voice_en_es.mp3","xm_transformer_600m-en_es-multi_domain"],
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["common_voice_en_ar.mp3","xm_transformer_600m-en_ar-multi_domain"],
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["common_voice_en_tr.mp3","xm_transformer_600m-en_tr-multi_domain"],
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["common_voice_en_fr.mp3","xm_transformer_600m-en_fr-multi_domain"],
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["common_voice_en_vi.mp3","xm_transformer_600m-en_vi-multi_domain"],
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]
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io1 = gr.Interface.load("huggingface/facebook/
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io2 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-ru_en-multi_domain")
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io3 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_ru-multi_domain")
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io4 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_es-multi_domain")
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io5 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_zh-multi_domain")
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io6 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-fr_en-multi_domain")
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io7 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_ar-multi_domain")
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io8 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_tr-multi_domain")
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io9 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_fr-multi_domain")
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io10 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_vi-multi_domain")
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def inference(text,model):
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outtext = io1(text)
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elif model == "xm_transformer_600m-ru_en-multi_domain":
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outtext = io2(text)
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elif model == "xm_transformer_600m-en_ru-multi_domain":
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outtext = io3(text)
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elif model == "xm_transformer_600m-en_es-multi_domain":
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outtext = io4(text)
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elif model == "xm_transformer_600m-en_zh-multi_domain":
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outtext = io5(text)
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elif model == "xm_transformer_600m-fr_en-multi_domain":
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outtext = io6(text)
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elif model == "xm_transformer_600m-en_ar-multi_domain":
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outtext = io7(text)
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elif model == "xm_transformer_600m-en_tr-multi_domain":
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outtext = io8(text)
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elif model == "xm_transformer_600m-en_fr-multi_domain":
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outtext = io9(text)
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else:
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outtext = io10(text)
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return outtext
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gr.Interface(
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inference,
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[gr.inputs.Audio(label="Input",type="filepath"),gr.inputs.Dropdown(choices=["
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],
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gr.outputs.Audio(label="Output"),
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article=article,
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import gradio as gr
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import numpy as np
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title = "Fairseq S2S"
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description = "Gradio Demo for fairseq S2S: speech-to-speech translation models. To use it, simply add your audio, or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.05604' target='_blank'>Direct speech-to-speech translation with discrete units</a> | <a href='https://github.com/facebookresearch/fairseq/tree/main/examples/speech_to_speech' target='_blank'>Github Repo</a></p>"
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examples = [
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["common_voice_es_en.flac","xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022"],
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]
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io1 = gr.Interface.load("huggingface/facebook/xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022")
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def inference(text,model):
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outtext = io1(text)
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return outtext
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gr.Interface(
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inference,
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[gr.inputs.Audio(label="Input",type="filepath"),gr.inputs.Dropdown(choices=["xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022"], type="value", default="xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022", label="model")
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],
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gr.outputs.Audio(label="Output"),
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article=article,
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