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ML solution for natural language text generation learned from text corpus using transformer model

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Novel Generator

Generative transformer model. Learns natural language from text corpus.

Tokenization

Training data and generated text encoded using ByteLevelBPETokenizer implemented by HuggingFace. Token dictionary needs to be generated beforehand from training, evaluation and test datasets. Resulting dictionary should be saved into JSON file.

Running

Currently only way to setup the process is by editing main.py scenario. There are a number of parameters at the beginning of the file which should be set. These include path to dictionary JSON-file, paths to files with corpus data for training, etc... There are also hyperparameters used to create the model and train and infer it.

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ML solution for natural language text generation learned from text corpus using transformer model

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