legacy-datasets/common_voice
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How to use adresgezgini/wav2vec-tr-lite-AG with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="adresgezgini/wav2vec-tr-lite-AG") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("adresgezgini/wav2vec-tr-lite-AG")
model = AutoModelForCTC.from_pretrained("adresgezgini/wav2vec-tr-lite-AG")YAML Metadata Error:"model-index[0].results[0].metrics[0].value" is required
The model can be used directly (without a language model) as follows:
import torch
import torchaudio
from datasets import load_dataset
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
test_dataset = load_dataset("common_voice", "tr", split="test[:2%]")
processor = Wav2Vec2Processor.from_pretrained("emre/wav2vec-tr-lite-AG")
model = Wav2Vec2ForCTC.from_pretrained("emre/wav2vec-tr-lite-AG")
resampler = torchaudio.transforms.Resample(48_000, 16_000)
**Test Result**: 27.30 %
[here](https://adresgezgini.com)