nguyenvulebinh
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README.md
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license: cc-by-nc-4.0
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# Vietnamese
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Since our model has the same architecture as the English wav2vec2 version, you can use [this notebook](https://colab.research.google.com/drive/1FjTsqbYKphl9kL-eILgUc-bl4zVThL8F?usp=sharing) for more information on how to fine-tune the model.
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nguyenvulebinh@gmail.com / binh@vietai.org
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[![Follow](https://img.shields.io/twitter/follow/nguyenvulebinh?style=social)](https://twitter.com/intent/follow?screen_name=nguyenvulebinh)
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license: cc-by-nc-4.0
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# Vietnamese Self-Supervised Learning Wav2Vec2 model
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## Model
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We use wav2vec2 architecture for doing Self-Supervised learning
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<img src="https://raw.githubusercontent.com/patrickvonplaten/scientific_images/master/wav2vec2.png" width=50% height=50%>
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## Data
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Our self-supervised model is pre-trained on a massive audio set of 13k hours of Vietnamese youtube audio, which includes:
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- Clean audio
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- Noise audio
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- Conversation
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- Multi-gender and dialects
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## Download
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We have already upload our pre-trained model to the Huggingface.
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- [Based version](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) ~ 95M params
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- [Large version](https://huggingface.co/nguyenvulebinh/wav2vec2-large-vi) ~ 317M params
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## Usage
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```python
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from transformers import Wav2Vec2ForPreTraining, Wav2Vec2Processor
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model_name = 'nguyenvulebinh/wav2vec2-base-vi'
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# model_name = 'nguyenvulebinh/wav2vec2-large-vi'
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model = Wav2Vec2ForPreTraining.from_pretrained(model_name)
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processor = Wav2Vec2Processor.from_pretrained(model_name)
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```
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Since our model has the same architecture as the English wav2vec2 version, you can use [this notebook](https://colab.research.google.com/drive/1FjTsqbYKphl9kL-eILgUc-bl4zVThL8F?usp=sharing) for more information on how to fine-tune the model.
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## Contact
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nguyenvulebinh@gmail.com / binh@vietai.org
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[![Follow](https://img.shields.io/twitter/follow/nguyenvulebinh?style=social)](https://twitter.com/intent/follow?screen_name=nguyenvulebinh)
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