---
license: mit
datasets:
- christopher/rosetta-code
pipeline_tag: text-classification
tags:
- code
---

This is a CoreML model for identification of following programming languages:

```go, lua, perl, python, apl, shell, c, c#, c++, cobol, lisp, erlang, fortran, groovy, haskell, java, javascript, kotlin, objective-c, pascal, php, powershell, r, ruby, rust, scala, scheme, swift, dart, sql, text, mysql, typescript, ecma, cmake, html, latex, jinja, json, toml, css```

It was trained on a cleaned up and filtered rosetta-code dataset (more precisely: https://huggingface.co/datasets/christopher/rosetta-code, but cleaned up).

## ProgrammingLanguageIdentificationV1
First version of PIL model. It was trained on 20 362 data points (including validation, which was picked automatically). 
Because each programming language has a different number of snippets (lowest: css, ecma, toml (1), highest: go (1110)) its accuracy varies a lot between languages. It's general accuracy is 98,8% for training and validation.

Future versions will focus on increasing dataset size.