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7097513
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Parent(s):
4314e4c
Update app.py
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app.py
CHANGED
@@ -4,7 +4,7 @@ import gradio as gr
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import pytube as pt
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from transformers import pipeline
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MODEL_NAME = "openai/whisper-
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device = 0 if torch.cuda.is_available() else "cpu"
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@@ -21,7 +21,7 @@ transcribe_token_id = all_special_ids[-5]
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translate_token_id = all_special_ids[-6]
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def transcribe(microphone, file_upload,
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warn_output = ""
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if (microphone is not None) and (file_upload is not None):
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warn_output = (
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@@ -34,7 +34,7 @@ def transcribe(microphone, file_upload, do_translate):
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file = microphone if microphone is not None else file_upload
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pipe.model.config.forced_decoder_ids = [[2,
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text = pipe(file)["text"]
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@@ -50,13 +50,13 @@ def _return_yt_html_embed(yt_url):
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return HTML_str
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def yt_transcribe(yt_url,
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yt = pt.YouTube(yt_url)
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html_embed_str = _return_yt_html_embed(yt_url)
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stream = yt.streams.filter(only_audio=True)[0]
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stream.download(filename="audio.mp3")
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pipe.model.config.forced_decoder_ids = [[2,
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text = pipe("audio.mp3")["text"]
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@@ -70,7 +70,7 @@ mf_transcribe = gr.Interface(
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inputs=[
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gr.inputs.Audio(source="microphone", type="filepath", optional=True),
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gr.inputs.Audio(source="upload", type="filepath", optional=True),
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gr.
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],
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outputs="text",
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layout="horizontal",
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@@ -86,7 +86,10 @@ mf_transcribe = gr.Interface(
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yt_transcribe = gr.Interface(
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fn=yt_transcribe,
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inputs=[
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outputs=["html", "text"],
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layout="horizontal",
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theme="huggingface",
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@@ -102,4 +105,5 @@ yt_transcribe = gr.Interface(
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with demo:
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gr.TabbedInterface([mf_transcribe, yt_transcribe], ["Transcribe Audio", "Transcribe YouTube"])
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demo.launch(enable_queue=True
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import pytube as pt
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from transformers import pipeline
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MODEL_NAME = "openai/whisper-large-v2"
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device = 0 if torch.cuda.is_available() else "cpu"
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translate_token_id = all_special_ids[-6]
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def transcribe(microphone, file_upload, task):
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warn_output = ""
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if (microphone is not None) and (file_upload is not None):
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warn_output = (
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file = microphone if microphone is not None else file_upload
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pipe.model.config.forced_decoder_ids = [[2, transcribe_token_id if task=="transcribe" else translate_token_id]]
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text = pipe(file)["text"]
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return HTML_str
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def yt_transcribe(yt_url, task):
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yt = pt.YouTube(yt_url)
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html_embed_str = _return_yt_html_embed(yt_url)
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stream = yt.streams.filter(only_audio=True)[0]
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stream.download(filename="audio.mp3")
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pipe.model.config.forced_decoder_ids = [[2, transcribe_token_id if task=="transcribe" else translate_token_id]]
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text = pipe("audio.mp3")["text"]
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inputs=[
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gr.inputs.Audio(source="microphone", type="filepath", optional=True),
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gr.inputs.Audio(source="upload", type="filepath", optional=True),
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gr.inputs.Radio(["transcribe", "translate"], label="task", default="transcribe"),
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],
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outputs="text",
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layout="horizontal",
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yt_transcribe = gr.Interface(
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fn=yt_transcribe,
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inputs=[
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gr.inputs.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
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gr.inputs.Radio(["transcribe", "translate"], label="task", default="transcribe")
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],
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outputs=["html", "text"],
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layout="horizontal",
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theme="huggingface",
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with demo:
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gr.TabbedInterface([mf_transcribe, yt_transcribe], ["Transcribe Audio", "Transcribe YouTube"])
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demo.launch(enable_queue=True)
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