WisdomShell/codeshell

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1621 stars · 116 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CodeShell is a family of 7-billion-parameter code large language models developed by PKU-KCL, trained on 500 billion tokens with an 8192-token context window, achieving strong HumanEval and MBPP results among 7B code models. The repository provides model weights (base, chat, and 4-bit quantized chat variants), a C++ runtime for GPU-free local deployment, and VS Code/JetBrains IDE plugins.

Use cases

• generate code from natural language prompts
• autocomplete code in VS Code or JetBrains IDEs
• run a code LLM locally on a CPU-only 8GB machine
• answer questions about code with a chat model
• quantize a code model to 4-bit for faster inference
• benchmark code models on HumanEval and MBPP
• self-host a coding assistant without sending code to the cloud

When to choose

• you need a compact 7B code model with competitive benchmark performance
• you want a fully open-stack coding assistant with IDE plugins and local C++ inference
• you must run a code LLM offline or on hardware without a GPU
• you prefer models downloadable from Chinese mirrors like ModelScope or WiseModel

When to avoid

• you need the absolute best code generation quality regardless of model size
• you require a permissively licensed model for commercial use without reviewing the custom license
• you need a actively updated model with recent training data
• you want a general-purpose assistant rather than a code-focused model

Facets

library · maturity maintenance

llm-inference machine-learning code-review developer-tools large-language-models artificial-intelligence developer-tools programming-languages python cpp cross-platform cli code-llm code-generation code-completion 7b-model quantization ide-plugin vscode jetbrains humaneval mbpp local-deployment chat-model gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="WisdomShell/codeshell")