legacy-datasets/common_voice
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How to use flax-community/wav2vec2-dhivehi with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="flax-community/wav2vec2-dhivehi") # Load model directly
from transformers import AutoProcessor, AutoModelForPreTraining
processor = AutoProcessor.from_pretrained("flax-community/wav2vec2-dhivehi")
model = AutoModelForPreTraining.from_pretrained("flax-community/wav2vec2-dhivehi")Wav2vec2 pre-pretrained from scratch using common voice dhivehi dataset. The model was trained with Flax during the Flax/Jax Community Week organised by HuggingFace.
The model used for training is Wav2Vec2 by FacebookAI. It was introduced in the paper "wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations" by Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, and Michael Auli (https://arxiv.org/abs/2006.11477).
This model is available in the 🤗 Model Hub.
Dhivehi data from Common Voice.
The dataset is also available in the 🤗 Datasets library.