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[Paper](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) | [Model](https://huggingface.co/bigcode/starcoder) | [Playground](https://huggingface.co/spaces/bigcode/bigcode-playground) | [VSCode](https://marketplace.visualstudio.com/items?itemName=HuggingFace.huggingface-vscode) | [Chat](https://huggingface.co/chat/?model=bigcode/starcoder)
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# What is this about?
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💫 StarCoder is a language model (LM) trained on source code and natural language text. Its training data incorporates more that 80 different programming languages as well as text extracted from github issues and commits and from notebooks. This repository showcases how we get an overview of this LM's capabilities.
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💫 StarCoder is a language model (LM) trained on source code and natural language text. Its training data incorporates more that 80 different programming languages as well as text extracted from GitHub issues and commits and from notebooks. This repository showcases how we get an overview of this LM's capabilities.
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# Disclaimer
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- [Merging PEFT adapter layers](#merging-peft-adapter-layers)
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# Quickstart
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StarCoder was trained on github code, thus it can be used to perform code generation. More precisely, the model can complete the implementation of a function or infer the following characters in a line of code. This can be done with the help of the 🤗's [transformers](https://github.com/huggingface/transformers) library.
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StarCoder was trained on GitHub code, thus it can be used to perform code generation. More precisely, the model can complete the implementation of a function or infer the following characters in a line of code. This can be done with the help of the 🤗's [transformers](https://github.com/huggingface/transformers) library.
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## Installation
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First, we have to install all the libraries listed in `requirements.txt`

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