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---
license: mit
tags:
- natural-language-processing
- code-generation
- torch
- lstm
---
This generative text model was trained using [Andrej Karpathy's code](https://github.com/karpathy/char-rnn) on homeworks by Linguistics students' homework assignments for a beginning Python course of HSE University.
Model was trained with size 512 and 3 layers, dropout 0.5.
## Usage
The procedure for installing the required software is described [by Karpathy](https://github.com/karpathy/char-rnn), torch is required, the code is written in lua. Be careful, versions of libraries written many years ago are used.
```bash
th sample.lua lm_lstm_epoch19.14_0.6292.t7 -length 10000 -temperature 0.5 -primetext 'some text'
```
## Train data
Train corpus consists of joined programms in to one file inclded in this repository as `input.txt`
## What for?
In an era of winning Transformers, ancient RNN models seem archaic. But I see that they still work better than modern architectures with such important categories from the humanities point of view as individual style.
This model was created just or fun of students at the end of the course.
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