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@ -8,6 +8,52 @@ This is the official PyTorch implementation for the following EMNLP 2021 paper f
![CodeT5 demo](codet5.gif)
## Updates
**Oct 25, 2021**
We release a CodeT5-base fine-tuned checkpoint ([Salesforce/codet5-base-multi-sum](https://huggingface.co/Salesforce/codet5-base-multi-sum)) for multi-lingual code summarzation. Below is how to use this model:
```python
from transformers import RobertaTokenizer, T5ForConditionalGeneration
if __name__ == '__main__':
tokenizer = RobertaTokenizer.from_pretrained('Salesforce/codet5-base')
model = T5ForConditionalGeneration.from_pretrained('Salesforce/codet5-base-multi-sum')
text = """def svg_to_image(string, size=None):
if isinstance(string, unicode):
string = string.encode('utf-8')
renderer = QtSvg.QSvgRenderer(QtCore.QByteArray(string))
if not renderer.isValid():
raise ValueError('Invalid SVG data.')
if size is None:
size = renderer.defaultSize()
image = QtGui.QImage(size, QtGui.QImage.Format_ARGB32)
painter = QtGui.QPainter(image)
renderer.render(painter)
return image"""
input_ids = tokenizer(text, return_tensors="pt").input_ids
generated_ids = model.generate(input_ids, max_length=20)
print(tokenizer.decode(generated_ids[0], skip_special_tokens=True))
# this prints: "Convert a SVG string to a QImage."
```
It significantly outperforms previous methods on code summarization in the [CodeXGLUE benchmark](https://github.com/microsoft/CodeXGLUE/tree/main/Code-Text/code-to-text):
| Model | Ruby | Javascript | Go | Python | Java | PHP | Overall |
| ----------- | :-------: | :--------: | :-------: | :-------: | :-------: | :-------: | :-------: |
| Seq2Seq | 9.64 | 10.21 | 13.98 | 15.93 | 15.09 | 21.08 | 14.32 |
| Transformer | 11.18 | 11.59 | 16.38 | 15.81 | 16.26 | 22.12 | 15.56 |
| [RoBERTa](https://arxiv.org/pdf/1907.11692.pdf) | 11.17 | 11.90 | 17.72 | 18.14 | 16.47 | 24.02 | 16.57 |
| [CodeBERT](https://arxiv.org/pdf/2002.08155.pdf) | 12.16 | 14.90 | 18.07 | 19.06 | 17.65 | 25.16 | 17.83 |
| [PLBART](https://aclanthology.org/2021.naacl-main.211.pdf) | 14.11 |15.56 | 18.91 | 19.30 | 18.45 | 23.58 | 18.32 |
| [CodeT5-base-multi-sum](https://arxiv.org/abs/2109.00859) | **15.24** | **16.18** | **19.95** | **20.42** | **20.26** | **26.10** | **19.69** |
**Oct 18, 2021**
We add a [model card](https://github.com/salesforce/CodeT5/blob/main/CodeT5_model_card.pdf) for CodeT5! Please reach out if you have any questions about it.
**Sep 24, 2021**
CodeT5 is now in [hugginface](https://huggingface.co/)!