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@@ -5,42 +5,28 @@ tags:
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  - automatic-speech-recognition
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  datasets:
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  - common_voice
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- widget:
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- - label: Librispeech sample 1
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- src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
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- - label: Librispeech sample 2
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- src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
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  ---
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  # Wav2Vec2 Spanish
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- Spanish Wav2Vec2 model pre-trained using the Spanish portion of the Common Voice dataset during the [Flax x Hugging Face](https://discss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) community event.
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-
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- Team:
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- [@mariagrandury](https://github.com/mariagrandury),
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- [@mrm8488](https://github.com/mrm8488),
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- [@edugp](https://github.com/edugp) and
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- [@pcuenq](https://github.com/pcuenq).
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  ## Model description
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- The model used for training is [Wav2Vec2] by FacebookAI. It was introduced in the paper
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  "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).
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  This model is available in the 🤗 [Model Hub](https://huggingface.co/facebook/wav2vec2-base-960h).
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- ## Intended uses & limitations
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-
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- ### How to use
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-
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- ### Limitations and bias
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-
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  ## Training data
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  Spanish portion of [Common Voice](https://commonvoice.mozilla.org/en/datasets). Common Voice is an open source, multi-language dataset of voices part of Mozilla's initiative to help teach machines how real people speak.
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  The dataset is also available in the 🤗 [Datasets](https://huggingface.co/datasets/common_voice) library.
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- ### Training procedure
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- ### Eval results
 
 
 
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  - automatic-speech-recognition
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  datasets:
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  - common_voice
 
 
 
 
 
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  ---
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  # Wav2Vec2 Spanish
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+ Wav2Vec2 model pre-trained using the Spanish portion of the Common Voice dataset. The model is trained with Flax and using TPUs sponsored by Google since this is part of the [Flax/Jax Community Week](https://discss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organised by HuggingFace.
 
 
 
 
 
 
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  ## Model description
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+ The model used for training is [Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) by FacebookAI. It was introduced in the paper
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  "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).
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  This model is available in the 🤗 [Model Hub](https://huggingface.co/facebook/wav2vec2-base-960h).
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  ## Training data
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  Spanish portion of [Common Voice](https://commonvoice.mozilla.org/en/datasets). Common Voice is an open source, multi-language dataset of voices part of Mozilla's initiative to help teach machines how real people speak.
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  The dataset is also available in the 🤗 [Datasets](https://huggingface.co/datasets/common_voice) library.
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+ ## Team members
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+ - María Grandury ([@mariagrandury](https://github.com/mariagrandury))
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+ - Manuel Romero ([@mrm8488](https://huggingface.co/mrm8488))
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+ - Eduardo González Ponferrada ([@edugp](https://huggingface.co/edugp))
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+ - pcuenq ([@pcuenq](https://huggingface.co/pcuenq))