In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.

Overview

Transformers are all you need

In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.

Table of Content

The workshop will be divided into four parts

  1. Introduction to Transformers as a HYPE
  2. Sneak peek to the theory behind Transfomers
  3. Quick tour (Huggingface framework)
  4. Lab

Note that you can always open the notebooks on Google Colab ( No need to install anything ) you just need a stable internet connection :

- fine tune a translation model Open In Colab

2. How to get started

  1. Fork this repository
  2. Create a branch by your name
  3. Go through the notebook and complete all tasks
  4. Submit a pull request

Homework exercise

Your task is to fine-tune a classification model

  1. Using HuggingFace transformers and datasets.
  2. fine tune it to one of the classification task of the GLUE Benchmark(CoLa to be specific).
  3. Use a checkpoint from the Hub ("distilbert-base-uncased" for example)
  4. Once finished submit a pull request to this repo, make sure to place your .ipynb file in the submissions folder (YOUR_NAME.ipynb)

Useful ressources : text_classification

Owner
Aymen Berriche
CS student at ESI Algiers | Dev Co-Manger at GDG Algiers | GitHub Campus Expert
Aymen Berriche
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