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Parent(s):
7487e83
Push app changes
Browse files- .gitignore +1 -0
- app.py +23 -0
- requirements.txt +3 -0
.gitignore
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/DeepLearning/myenv
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app.py
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import torch
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from transformers import pipeline
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from datasets import load_dataset
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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pipe = pipeline(
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"automatic-speech-recognition",
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model="openai/whisper-small",
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chunk_length_s=30,
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device=device,
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)
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ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
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sample = ds[0]["audio"]
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prediction = pipe(sample.copy(), batch_size=8)["text"]
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# we can also return timestamps for the predictions
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prediction = pipe(sample.copy(), batch_size=8, return_timestamps=True)["chunks"]
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print(prediction[0]['text'])
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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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