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Transformers kit - Multi-task QA/Tagging/Multi-label Multi-Class Classification/Generation with BERT/ALBERT/T5/BERT
TFKit is a tool kit mainly for language generation.
It leverages the use of transformers on many tasks with different models in this all-in-one framework.
All you need is a little change of config.
With transformer models - BERT/ALBERT/T5/BART......
Text Generation | :memo: seq2seq language model |
Text Generation | :pen: causal language model |
Text Generation | :printer: once generation model / once generation model with ctc loss |
Text Generation | :pencil: onebyone generation model |
Learn more from the document.
Simple installation from PyPI
pip install git+https://github.com/voidful/TFkit.git@refactor-dataset
input, target
tfkit-train \
--task clas \
--config xlm-roberta-base \
--train training_data.csv \
--test testing_data.csv \
--lr 4e-5 \
--maxlen 384 \
--epoch 10 \
--savedir roberta_sentiment_classificer
tfkit-eval \
--task roberta_sentiment_classificer/1.pt \
--metric clas \
--valid testing_data.csv
tfkit-train \
--task clas clas \
--config xlm-roberta-base \
--train training_data_taskA.csv training_data_taskB.csv \
--test testing_data_taskA.csv testing_data_taskB.csv \
--lr 4e-5 \
--maxlen 384 \
--epoch 10 \
--savedir roberta_sentiment_classificer_multi_task
Due to time constraints, the following tasks are temporarily not supported
Classification | :label: multi-class and multi-label classification |
Question Answering | :page_with_curl: extractive qa |
Question Answering | :radio_button: multiple-choice qa |
Tagging | :eye_speech_bubble: sequence level tagging / sequence level with crf |
Self-supervise Learning | :diving_mask: mask language model |
Thanks for your interest.There are many ways to contribute to this project. Get started here.
Icons modify from Freepik from www.flaticon.com
Icons modify from Nikita Golubev from www.flaticon.com
FAQs
Transformers kit - Multi-task QA/Tagging/Multi-label Multi-Class Classification/Generation with BERT/ALBERT/T5/BERT
We found that tfkit demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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