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simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quickly train your T5 models.

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Quickly train T5/mT5/byT5 models in just 3 lines of code

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simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.

T5 models can be used for several NLP tasks such as summarization, QA , QG , translation , text generation, and more.

Here's a link to Medium article along with an example colab notebook


# It's advisable to create a new python environment and install simplet5
pip install --upgrade simplet5


simpleT5 for summarization task Open In Collab

# import
from simplet5 import SimpleT5

# instantiate
model = SimpleT5()

# load (supports t5, mt5, byT5 models)

# train
model.train(train_df=train_df, # pandas dataframe with 2 columns: source_text & target_text
            eval_df=eval_df, # pandas dataframe with 2 columns: source_text & target_text
            source_max_token_len = 512, 
            target_max_token_len = 128,
            batch_size = 8,
            max_epochs = 5,
            use_gpu = True,
            outputdir = "outputs",
            early_stopping_patience_epochs = 0,
            precision = 32

# load trained T5 model
model.load_model("t5","path/to/trained/model/directory", use_gpu=False)

# predict
model.predict("input text for prediction")



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