Fix: Replace deprecated cached_path usage with hf_hub_download
#2
by
anon-repair-bot
- opened
README.md
CHANGED
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@@ -64,21 +64,28 @@ Usage
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#!pip install transformers==4.20.0
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#!pip install https://github.com/kpu/kenlm/archive/master.zip
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#!pip install pyctcdecode==0.4.0
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from transformers.file_utils import cached_path, hf_bucket_url
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from importlib.machinery import SourceFileLoader
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from transformers import Wav2Vec2ProcessorWithLM
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from IPython.
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import torchaudio
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import torch
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# Load model & processor
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model_name = "nguyenvulebinh/wav2vec2-base-vi-vlsp2020"
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# model_name = "nguyenvulebinh/wav2vec2-large-vi-vlsp2020"
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model = SourceFileLoader("model", cached_path(hf_bucket_url(model_name,filename="model_handling.py"))).load_module().Wav2Vec2ForCTC.from_pretrained(model_name)
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processor = Wav2Vec2ProcessorWithLM.from_pretrained(model_name)
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# Load an example audio (16k)
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audio, sample_rate = torchaudio.load(cached_path(hf_bucket_url(model_name, filename="t2_0000006682.wav")))
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input_data = processor.feature_extractor(audio[0], sampling_rate=16000, return_tensors='pt')
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# Infer
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#!pip install transformers==4.20.0
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#!pip install https://github.com/kpu/kenlm/archive/master.zip
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#!pip install pyctcdecode==0.4.0
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#from transformers.file_utils import cached_path, hf_bucket_url
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from huggingface_hub import hf_hub_download
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from importlib.machinery import SourceFileLoader
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from transformers import Wav2Vec2ProcessorWithLM
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from IPython.display import Audio
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import torchaudio
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import torch
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import kenlm
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# Load model & processor
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model_name = "nguyenvulebinh/wav2vec2-base-vi-vlsp2020"
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# model_name = "nguyenvulebinh/wav2vec2-large-vi-vlsp2020"
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#model = SourceFileLoader("model", cached_path(hf_bucket_url(model_name,filename="model_handling.py"))).load_module().Wav2Vec2ForCTC.from_pretrained(model_name)
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#processor = Wav2Vec2ProcessorWithLM.from_pretrained(model_name)
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model_file = hf_hub_download(model_name, filename="model_handling.py")
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audio_file = hf_hub_download(model_name, filename="t2_0000006682.wav")
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# Load an example audio (16k)
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#audio, sample_rate = torchaudio.load(cached_path(hf_bucket_url(model_name, filename="t2_0000006682.wav")))
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audio, sample_rate = torchaudio.load(audio_file)
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input_data = processor.feature_extractor(audio[0], sampling_rate=16000, return_tensors='pt')
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# Infer
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