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Browse files- README.md +4 -4
- app.py +20 -0
- requirements.txt +3 -0
README.md
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---
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title:
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emoji:
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sdk: gradio
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sdk_version: 3.12.0
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app_file: app.py
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---
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title: ID2223 Lab2 Whisper
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emoji: 🐨
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colorFrom: purple
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colorTo: purple
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sdk: gradio
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sdk_version: 3.12.0
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app_file: app.py
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app.py
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from transformers import pipeline
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import gradio as gr
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pipe1 = pipeline(model="khalidey/ID2223_Lab2_Whisper_SV") # change to "your-username/the-name-you-picked"
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pipe2 = pipeline('text-generation', model='birgermoell/swedish-gpt')
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def transcribe(audio):
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text = pipe1(audio)["text"]
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generated_text = pipe2(text, max_length = 30, num_return_sequences=2)[0]['generated_text']
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return text, generated_text
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iface = gr.Interface(
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fn=transcribe,
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inputs=gr.Audio(source="microphone", type="filepath"),
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outputs=['text', 'text'],
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title="Whisper Small Swedish + Swedish GPT",
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description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model and text generation with Swedish GPT.",
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)
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iface.launch()
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requirements.txt
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gradio
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transformers
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torch
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