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Update README.md

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@@ -71,32 +71,7 @@ Use the code below to get started with the model.
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  ## Running the model
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- <details>
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- ```python
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- from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
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- import torch
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- import torchaudio
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-
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- model_id = "fastinom/ASR_fassy"
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- model = Wav2Vec2ForCTC.from_pretrained(model_id)
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- processor = Wav2Vec2Processor.from_pretrained(model_id)
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-
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- def load_audio(file_path):
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- speech_array, sampling_rate = torchaudio.load(file_path)
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- resampler = torchaudio.transforms.Resample(sampling_rate, 16000)
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- speech = resampler(speech_array).squeeze().numpy()
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- return speech
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- audio_file = "/content/drive/MyDrive/recordings/wavefiles/1.wav"
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- speech = load_audio(audio_file)
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-
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- inputs = processor(speech, sampling_rate=16000, return_tensors="pt", padding=True)
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- with torch.no_grad():
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- logits = model(inputs.input_values).logits
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- predicted_ids = torch.argmax(logits, dim=-1)
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- transcription = processor.batch_decode(predicted_ids)
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- print(transcription[0])
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- </details>
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- ```python
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  ## Training Details
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  ### Training Data
 
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  ## Running the model
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  ## Training Details
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  ### Training Data