Add dotenv
, fixed requirements.txt
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.env.sample
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.env.sample
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MODEL="m3hrdadfi/wav2vec2-large-xlsr-persian"
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LOG_LEVEL="INFO"
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main.py
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main.py
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import logging
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import os
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import warnings
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import librosa
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import transformers
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import torch
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from dotenv import load_dotenv
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from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
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# MODEL = "m3hrdadfi/wav2vec2-large-xlsr-persian"
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MODEL = "/home/reza/data/huggingface-models/04.wav2vec2-large-xlsr-persian"
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warnings.filterwarnings("ignore")
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transformers.logging.set_verbosity_error()
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load_dotenv()
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MODEL = os.getenv("MODEL", "m3hrdadfi/wav2vec2-large-xlsr-persian")
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LOG_LEVEL = os.getenv("LOG_LEVEL", "DEBUG")
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def initLogger(name=__name__, level=logging.DEBUG):
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if name[:2] == '__' and name[-2:] == '__':
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name = name[2:-2]
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logger = logging.getLogger(name)
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def initLogger():
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logger = logging.getLogger("speech2text-fa")
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level = getattr(logging, LOG_LEVEL.upper())
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fmt = '%(asctime)s | %(levelname)-8s | %(name)s | %(message)s'
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datefmt = '%Y-%m-%d %H:%M:%S'
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fmt = "%(asctime)s | %(levelname)-8s | %(message)s"
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datefmt = "%Y-%m-%d %H:%M:%S"
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ch = logging.StreamHandler()
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ch.setLevel(logging.DEBUG)
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formatter = logging.Formatter(fmt, datefmt)
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@ -49,7 +56,7 @@ def mp3_to_text(mp3_file_path):
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if __name__ == "__main__":
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logger = initLogger('speech2text_fa', level=logging.INFO)
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logger = initLogger()
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text = mp3_to_text("samples/sample1.wav")
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print()
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print(text)
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torch==2.1.1+cpu
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torchaudio==2.1.1+cpu
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transformers==4.35.2
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https://download.pytorch.org/whl/cpu/torch-2.1.1%2Bcpu-cp311-cp311-linux_x86_64.whl#sha256=d83b13cb17544f9851cc31fed197865eae0c0f5d32df9d8d6d8535df7d2e5109
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https://download.pytorch.org/whl/cpu/torchaudio-2.1.1%2Bcpu-cp311-cp311-linux_x86_64.whl#sha256=e0eb276958fcbd7c88f5daf761823e36ce5e41332d40f9e01fb49d80d7cc1bb1
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librosa==0.10.1
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--find-links https://download.pytorch.org/whl/cpu
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python-dotenv==1.0.0
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tokenizers>=0.10.1,<0.11
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transformers>=4.16.2,<4.17.0
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