101 lines
2.6 KiB
Markdown
101 lines
2.6 KiB
Markdown
---
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language: code
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thumbnail:
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---
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# CodeBERTaJS
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CodeBERTaJS is a RoBERTa-like model trained on the [CodeSearchNet](https://github.blog/2019-09-26-introducing-the-codesearchnet-challenge/) dataset from GitHub for `javaScript` by [Manuel Romero](https://twitter.com/mrm8488)
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The **tokenizer** is a Byte-level BPE tokenizer trained on the corpus using Hugging Face `tokenizers`.
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Because it is trained on a corpus of code (vs. natural language), it encodes the corpus efficiently (the sequences are between 33% to 50% shorter, compared to the same corpus tokenized by gpt2/roberta).
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The (small) **model** is a 6-layer, 84M parameters, RoBERTa-like Transformer model – that’s the same number of layers & heads as DistilBERT – initialized from the default initialization settings and trained from scratch on the full `javascript` corpus (120M after preproccessing) for 2 epochs.
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## Quick start: masked language modeling prediction
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```python
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JS_CODE = """
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async function createUser(req, <mask>) {
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if (!validUser(req.body.user)) {
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return res.status(400);
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}
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user = userService.createUser(req.body.user);
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return res.json(user);
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}
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""".lstrip()
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```
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### Does the model know how to complete simple JS/express like code?
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```python
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from transformers import pipeline
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fill_mask = pipeline(
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"fill-mask",
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model="mrm8488/codeBERTaJS",
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tokenizer="mrm8488/codeBERTaJS"
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)
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fill_mask(JS_CODE)
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## Top 5 predictions:
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#
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'res' # prob 0.069489665329
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'next'
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'req'
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'user'
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',req'
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```
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### Yes! That was easy 🎉 Let's try with another example
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```python
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JS_CODE_= """
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function getKeys(obj) {
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keys = [];
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for (var [key, value] of Object.entries(obj)) {
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keys.push(<mask>);
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}
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return keys
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}
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""".lstrip()
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```
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Results:
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```python
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'obj', 'key', ' value', 'keys', 'i'
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```
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> Not so bad! Right token was predicted as second option! 🎉
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## This work is heavely inspired on [codeBERTa](https://github.com/huggingface/transformers/blob/master/model_cards/huggingface/CodeBERTa-small-v1/README.md) by huggingface team
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<br>
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## CodeSearchNet citation
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<details>
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```bibtex
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@article{husain_codesearchnet_2019,
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title = {{CodeSearchNet} {Challenge}: {Evaluating} the {State} of {Semantic} {Code} {Search}},
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shorttitle = {{CodeSearchNet} {Challenge}},
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url = {http://arxiv.org/abs/1909.09436},
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urldate = {2020-03-12},
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journal = {arXiv:1909.09436 [cs, stat]},
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author = {Husain, Hamel and Wu, Ho-Hsiang and Gazit, Tiferet and Allamanis, Miltiadis and Brockschmidt, Marc},
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month = sep,
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year = {2019},
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note = {arXiv: 1909.09436},
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}
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```
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</details>
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> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488)
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> Made with <span style="color: #e25555;">♥</span> in Spain
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