[PolyCoder](https://github.com/VHellendoorn/Code-LMs) uses GPT2 architecture, with BPE tokenizer trained on a random 5% subset of the data (all languages), and a context length of 2048. To study the effect of scaling of model size, the odel was trained in 3 different sizes.

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|Model | # parameters | 
|   -   |   -  | 
| GPT2 | 160M |
| GPT2 | 400M |
| GPT2 | 2.7B |

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PolyCoder is currently being integrated in 🤗 `transformers`. Meanwhile it can be loaded following the instructions in the original GitHub [repo](https://github.com/vhellendoorn/code-lms#models).