simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quickly train your T5 models.
Quickly train T5/mT5/byT5 models in just 3 lines of code
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
# import from simplet5 import SimpleT5 # instantiate model = SimpleT5() # load (supports t5, mt5, byT5 models) model.from_pretrained("t5","t5-base") # 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")
- Geek Culture: simpleT5 — Train T5 Models in Just 3 Lines of Code
- Abstractive Summarization with SimpleT5⚡️
- Training T5 model in just 3 lines of Code with ONNX Inference
- Kaggle: simpleT5⚡️ - Generating one line summary of papers
- Youtube: Abstractive Summarization Demo with SimpleT5
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simplet5-0.1.4.tar.gz (7.3 kB view hashes)