MLNLP-World/LLMs-from-scratch-CN

LLMs-from-scratch项目中文翻译

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MLNLP-World/LLMs-from-scratch-CN has 3k+ stars and 500+ forks on GitHub, is written in Jupyter Notebook, and was last pushed on Apr 19, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 17 minutes ago
Added to GitGenius on September 30th, 2026
Created on January 20th, 2025
Open Issues & Pull Requests: 2 (+0)
GitHub issues: Enabled
Number of forks: 515
Total Stargazers: 3,032 (+0)
Total Subscribers: 25 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 20.3 hours
Mean response time: 20.3 hours
90th percentile: 20.3 hours
Tracked items: 1

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Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 267 days
Stale 30+ days: 1
Stale 90+ days: 1

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Comments in 7 days: 0
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Detailed Description

LLMs-from-scratch-cn is a Chinese translation of educational material that teaches large language model development from foundational principles.

The project addresses the need for LLM learning resources accessible to Chinese-speaking developers. It translates detailed markdown notes and Jupyter notebook code from an English-language original, maintaining accuracy while adapting phrasing and structure to suit Chinese reading conventions. The Jupyter code includes extensive Chinese-language comments to help learners understand and implement concepts practically. The translation is accompanied by supplementary materials designed to expand knowledge beyond the core content.

This resource suits Chinese-language learners seeking to understand how large language models work from first principles, rather than treating them as isolated from traditional machine learning. It works best for those who prefer learning through detailed explanations and annotated code examples. The project explicitly positions itself as a translation and learning aid rather than an extension or modification of the original material.

The project is in active development with contributions welcomed from the community. The maintainers acknowledge potential imperfections in the translation and invite feedback for improvement. The effort reflects a commitment to making LLM education more accessible within the Chinese-speaking developer community.