Tôi đã fine-tune với 15Gb dữ liệu audio với kết quả Wer: 24.46

Cách sử dụng


import torch
from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
import torchaudio

mydevice = 'cuda'
processor = Wav2Vec2Processor.from_pretrained("hataphu/wav2vec2-vi-300m")
model = Wav2Vec2ForCTC.from_pretrained("hataphu/wav2vec2-vi-300m")
model.to(mydevice)
model.eval()
audio_input, sampling_rate = torchaudio.load('audio-path-file')

input_values = processor(
    audio_input.squeeze().numpy(), sampling_rate=sampling_rate
).input_values[0]

logits = model(torch.tensor(input_values).unsqueeze(0).to(mydevice)).logits
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.decode(predicted_ids[0])
print(transcription)
Downloads last month
28
Safetensors
Model size
316M params
Tensor type
F32
·
Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for hataphu/wav2vec2-vi-300m

Finetuned
(522)
this model