Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
700fda9
1
Parent(s):
dee3b49
u1
Browse files
app.py
CHANGED
@@ -63,14 +63,33 @@ def transcribe(audio_file):
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return f"Error during transcription: {str(e)}"
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# Create Gradio interface
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fn=transcribe,
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inputs=
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)
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def install_requirements():
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requirements_path = 'requirements.txt'
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@@ -116,7 +135,7 @@ if __name__ == "__main__":
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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MODEL_NAME = "alakxender/wav2vec2-large-mms-1b-dv-syn-md" # Trained on 100% Synthetic Data (
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# MODEL_NAME = "alakxender/wav2vec2-large-mms-1b-cv" # Trained on Common Voice Data (Unknown Hours)
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# MODEL_NAME = "alakxender/whisper-small-dv-syn-md" # Trained on 100% Synthetic Data (150 Hours)
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# MODEL_NAME = "alakxender/whisper-small-cv" # Trained on Common Voice Data (Unknown Hours)
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@@ -142,6 +161,6 @@ if __name__ == "__main__":
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MAX_LENGTH = 120 # 2 minutes
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MIN_LENGTH = 1 # 1 second
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else:
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print("Failed to install some requirements")
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return f"Error during transcription: {str(e)}"
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# Create Gradio interface
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css = """
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.textbox1 textarea {
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font-size: 18px !important;
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font-family: 'MV_Faseyha', 'Faruma', 'A_Faruma' !important;
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line-height: 1.8 !important;
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}
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.textbox2 textarea {
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display: none;
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}
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"""
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demo = gr.Blocks(css=css)
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tab_audio = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(sources=["upload","microphone"], type="filepath", label="Audio"),
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],
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outputs=gr.Textbox(label="Transcription", rtl=True, elem_classes="textbox1"),
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title="Transcribe Dhivehi Audio",
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allow_flagging="never",
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)
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with demo:
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gr.TabbedInterface([tab_audio], ["Audio"])
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def install_requirements():
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requirements_path = 'requirements.txt'
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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MODEL_NAME = "alakxender/wav2vec2-large-mms-1b-dv-syn-md" # Trained on 100% Synthetic Data (150 Hours)
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# MODEL_NAME = "alakxender/wav2vec2-large-mms-1b-cv" # Trained on Common Voice Data (Unknown Hours)
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# MODEL_NAME = "alakxender/whisper-small-dv-syn-md" # Trained on 100% Synthetic Data (150 Hours)
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# MODEL_NAME = "alakxender/whisper-small-cv" # Trained on Common Voice Data (Unknown Hours)
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MAX_LENGTH = 120 # 2 minutes
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MIN_LENGTH = 1 # 1 second
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demo.launch()
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else:
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print("Failed to install some requirements")
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