Update README.md

README.md

@@ -1,3 +1,46 @@
 ---
 license: mit
+datasets:
+- Wannita/PyCoder
+metrics:
+- accuracy
+- bleu
+- meteor
+- exact_match
+- rouge
+library_name: transformers
+pipeline_tag: text-generation
 ---
+# PyCoder
+
+This repository contains the model for the paper [Syntax-Aware On-the-Fly Code Completion](https://arxiv.org/abs/2211.04673)
+
+The sample code to run the model can be found in directory: "`assets/notebooks/inference.ipynb`" in our GitHub: https://github.com/awsm-research/pycoder.
+
+PyCoder is an auto code completion model which leverage a Multi-Task Training technique (MTT) to cooperatively
+learn the code prediction task and the type prediction task. For the type prediction
+task, we propose to leverage the standard Python token
+type information (e.g., String, Number, Name, Keyword),
+which is readily available and lightweight, instead of using
+the AST information which requires source code to be parsable for an extraction, limiting its ability to perform on-the-fly code completion (see Section 2.3 in our paper). 
+
+More information can be found in our paper.
+
+If you use our code or PyCoder, please cite our paper.
+
+<pre><code>@article{takerngsaksiri2022syntax,
+  title={Syntax-Aware On-the-Fly Code Completion},
+  author={Takerngsaksiri, Wannita and Tantithamthavorn, Chakkrit and Li, Yuan-Fang},
+  journal={arXiv preprint arXiv:2211.04673},
+  year={2022}
+}</code></pre>
+
+---
+license: mit
+datasets:
+- Wannita/PyCoder
+metrics:
+- accuracy
+library_name: transformers
+pipeline_tag: text-generation
+---