Easily train your own text-generating neural network of any size and complexity

## Project description

Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly train on a text using a pretrained model.

• A modern neural network architecture which utilizes new techniques as attention-weighting and skip-embedding to accelerate training and improve model quality.
• Able to train on and generate text at either the character-level or word-level.
• Able to configure RNN size, the number of RNN layers, and whether to use bidirectional RNNs.
• Able to train on any generic input text file, including large files.
• Able to train models on a GPU and then use them with a CPU.
• Able to utilize a powerful CuDNN implementation of RNNs when trained on the GPU, which massively speeds up training time as opposed to normal LSTM implementations.
• Able to train the model using contextual labels, allowing it to learn faster and produce better results in some cases.
• Able to generate text interactively for customized stories.

## Project details

### Source Distribution

textgenrnn-2.0.0.tar.gz (1.7 MB view hashes)

Uploaded source