patrickvonplaten / data2vec-base

huggingface.co
Total runs: 11
24-hour runs: 0
7-day runs: -8
30-day runs: -6
Model's Last Updated: April 19 2022
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Introduction of data2vec-base

Model Details of data2vec-base

Data2Vec-Audio-Base

Facebook's Data2Vec

The base model pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz.

Note : This model does not have a tokenizer as it was pretrained on audio alone. In order to use this model speech recognition , a tokenizer should be created and the model should be fine-tuned on labeled text data. Check out this blog for more in-detail explanation of how to fine-tune the model.

Paper

Authors: Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, Michael Auli

Abstract

While the general idea of self-supervised learning is identical across modalities, the actual algorithms and objectives differ widely because they were developed with a single modality in mind. To get us closer to general self-supervised learning, we present data2vec, a framework that uses the same learning method for either speech, NLP or computer vision. The core idea is to predict latent representations of the full input data based on a masked view of the input in a self-distillation setup using a standard Transformer architecture. Instead of predicting modality-specific targets such as words, visual tokens or units of human speech which are local in nature, data2vec predicts contextualized latent representations that contain information from the entire input. Experiments on the major benchmarks of speech recognition, image classification, and natural language understanding demonstrate a new state of the art or competitive performance to predominant approaches.

The original model can be found under https://github.com/pytorch/fairseq/tree/main/examples/data2vec .

Pre-Training method

model image

For more information, please take a look at the official paper .

Usage

See this notebook for more information on how to fine-tune the model.

Runs of patrickvonplaten data2vec-base on huggingface.co

11
Total runs
0
24-hour runs
-1
3-day runs
-8
7-day runs
-6
30-day runs

More Information About data2vec-base huggingface.co Model

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data2vec-base huggingface.co

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https://huggingface.co/patrickvonplaten/data2vec-base

data2vec-base install

data2vec-base is an open source model from GitHub that offers a free installation service, and any user can find data2vec-base on GitHub to install. At the same time, huggingface.co provides the effect of data2vec-base install, users can directly use data2vec-base installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

data2vec-base install url in huggingface.co:

https://huggingface.co/patrickvonplaten/data2vec-base

Url of data2vec-base

Provider of data2vec-base huggingface.co

patrickvonplaten
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