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Upgrade deps
Browse files- README.md +1 -1
- app.py +8 -10
- requirements.txt +4 -3
README.md
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@@ -4,7 +4,7 @@ emoji: 🔥
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colorFrom: pink
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colorTo: blue
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned: false
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---
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colorFrom: pink
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colorTo: blue
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sdk: gradio
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sdk_version: 5.21.0
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app_file: app.py
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pinned: false
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---
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app.py
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@@ -6,6 +6,7 @@ from transformers import pipeline
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from transformers.pipelines.audio_utils import ffmpeg_read
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import tempfile
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import os
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MODEL_NAME = "dataprizma/whisper-large-v3-turbo"
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mf_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.
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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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theme="huggingface",
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title="Whisper Large V3: Transcribe Audio",
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description=(
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@@ -109,11 +109,10 @@ mf_transcribe = gr.Interface(
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file_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.
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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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theme="huggingface",
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title="Whisper Large V3: Transcribe Audio",
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description=(
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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.
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gr.
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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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title="Whisper Large V3: Transcribe YouTube",
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description=(
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with demo:
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gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
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demo.launch(
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from transformers.pipelines.audio_utils import ffmpeg_read
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import tempfile
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import time
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import os
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MODEL_NAME = "dataprizma/whisper-large-v3-turbo"
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mf_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(type="filepath"),
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gr.Radio(["transcribe", "translate"], label="Task"),
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],
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outputs="text",
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theme="huggingface",
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title="Whisper Large V3: Transcribe Audio",
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description=(
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file_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(type="filepath", label="Audio file"),
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gr.Radio(["transcribe", "translate"], label="Task"),
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],
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outputs="text",
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theme="huggingface",
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title="Whisper Large V3: Transcribe Audio",
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description=(
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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.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
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gr.Radio(["transcribe", "translate"], label="Task")
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],
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outputs=["html", "text"],
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theme="huggingface",
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title="Whisper Large V3: Transcribe YouTube",
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description=(
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with demo:
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gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
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demo.launch()
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requirements.txt
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torch
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yt-dlp
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transformers==4.49.0
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torch==2.6.0
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yt-dlp==2025.2.19
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gradio==5.21.0
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