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Being towards death

Heed not to the tree-rustling and leaf-lashing rain, Why not stroll along, whistle and sing under its rein. Lighter and better suited than horses are straw sandals and a bamboo staff, Who's afraid? A palm-leaf plaited cape provides enough to misty weather in life sustain. A thorny spring breeze sobers up the spirit, I feel a slight chill, The setting sun over the mountain offers greetings still. Looking back over the bleak passage survived, The return in time Shall not be affected by windswept rain or shine.
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Install your personal code assistant now! CodeShell, the most powerful code AI model developed by Peking University, is open source! (Installation method for vscode plugin included)

#技术#AI369
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CodeShell is a code model developed by the Knowledge Computing Laboratory of the National Engineering Research Center for Software Engineering at Peking University, in collaboration with the AI Laboratory of Sichuan Tianfu Bank. It is a code model with 7 billion parameters and is known as the "most powerful code base of its size". CodeShell aims to provide intelligent programming support, including code generation, completion, correction, refactoring, commenting, documentation, and evaluation. It supports multiple programming languages and can also generate code based on natural language descriptions or convert code between different languages. To use CodeShell, users need to install the plugin in VS Code and follow the instructions on the official website. The plugin can be used for code autocompletion and other features. The CodeShell model and evaluation are open-source and can be found on GitHub.

CodeShell is a code model developed by the Knowledge Computing Laboratory of the National Engineering Research Center for Software Engineering at Peking University in collaboration with the AI Laboratory of Sichuan Tianfu Bank. It is a large-scale model with 7 billion parameters, known as the "most powerful code base of its size".

CodeShell was trained on 500 billion tokens and has a context window length of 8192. Its architecture combines the core features of StarCoder and Llama.

The goal of CodeShell is to provide full-stack intelligent programming support, including code generation, code completion, code correction, code refactoring, code commenting, code documentation, and code evaluation.

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CodeShell supports multiple programming languages, including Python, Java, C#, C++, JavaScript, HTML, CSS, SQL, etc. CodeShell can also generate code based on natural language descriptions or generate natural language descriptions based on code. It can also perform cross-language conversion, transforming code from one language to another.

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How to use CodeShell?

Using CodeShell is very simple. Just install the CodeShell plugin in VS Code and you can directly access CodeShell's features in the editor.

Many people may directly search for CodeShell in VS Code! But the search results are wrong!

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This is wrong! Wrong! Wrong!

The correct way is to follow the steps in the official website's introduction and download and install it!

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After executing the command, you will see this file in the folder: codeshell-vscode-0.0.1.vsix

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Drag this file to the vscode plugin area and it will be automatically installed. After installation, an instruction page will open. This is the correct way!

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Then you need to configure the plugin's code autocompletion feature.

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By completing these steps, you have installed the plugin, but you still need to deploy the large model.

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According to the official instructions, after completing these steps, you can run it. However, during the cloning process, the author kept experiencing timeouts and it is unknown whether it is due to the popularity of the large model or the excessive number of downloads. Interested friends can try it themselves and see if they can successfully deploy it!

CodeShell open source repository:
https://github.com/WisdomShell/codeshell

CodeShell's VSCode plugin open source repository:
https://github.com/WisdomShell/codeshell-vscode

CodeShell base model:
https://huggingface.co/WisdomShell/CodeShell-7B

Evaluation open source repository:
https://github.com/WeOpenML/PandaLM

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