REPOGEO REPORT · LITE

skindhu/Build-A-Large-Language-Model-CN

Default branch main · commit 592cc35a · scanned 6/30/2026, 2:43:28 AM

GitHub: 3,785 stars · 635 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

22 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface skindhu/Build-A-Large-Language-Model-CN, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

hightopics#1

Add relevant topics to the repository

Why:

COPY-PASTE FIX

large-language-models, llm, gpt, deep-learning, machine-learning, nlp, chinese, tutorial, e-book, from-scratch

highreadme#2

Add a concise introductory sentence to the README

Why:

CURRENT

# Build a Large Language Model (From Scratch) 中文版

随着大语言模型（LLM）技术的飞速发展，越来越多的应用开始渗透到我们的工作和日常生活中。

COPY-PASTE FIX

# Build a Large Language Model (From Scratch) 中文版

本项目是《Build a Large Language Model (From Scratch)》的中文翻译版，一本深入探讨大语言模型原理与实现的开源电子书。随着大语言模型（LLM）技术的飞速发展，越来越多的应用开始渗透到我们的工作和日常生活中。

mediumreadme#3

Clarify the repository's license in the README

Why:

COPY-PASTE FIX

## 许可证

本项目采用自定义许可证。请查阅 `LICENSE` 文件以获取完整的许可条款和条件。

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface skindhu/Build-A-Large-Language-Model-CN

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

huggingface/transformers

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers · recommended 1×
Stanford CS324 · recommended 1×
DeepLearning.AI's Generative AI with Transformers Specialization · recommended 1×
pytorch/pytorch · recommended 1×
tensorflow/tensorflow · recommended 1×

CATEGORY QUERY
Where can I find a comprehensive guide to building large language models from scratch?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers Library (huggingface/transformers)
2. Stanford CS324
3. DeepLearning.AI's Generative AI with Transformers Specialization
4. PyTorch (pytorch/pytorch)
5. TensorFlow (tensorflow/tensorflow)
AI recommended 5 alternatives but never named skindhu/Build-A-Large-Language-Model-CN. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking practical tutorials to implement large language models and understand GPT architecture in Chinese.
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers
2. PyTorch
3. TensorFlow
4. "动手学深度学习" (Dive into Deep Learning)
5. Bilibili (哔哩哔哩)
6. Zhihu (知乎)
7. CSDN (中国软件开发网)
8. OpenAI's GPT-3/GPT-4 API Documentation
AI recommended 8 alternatives but never named skindhu/Build-A-Large-Language-Model-CN. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of skindhu/Build-A-Large-Language-Model-CN?
pass
AI did not name skindhu/Build-A-Large-Language-Model-CN — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts skindhu/Build-A-Large-Language-Model-CN in production, what risks or prerequisites should they evaluate first?
pass
AI named skindhu/Build-A-Large-Language-Model-CN explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo skindhu/Build-A-Large-Language-Model-CN solve, and who is the primary audience?
pass
AI did not name skindhu/Build-A-Large-Language-Model-CN — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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HTML

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skindhu/Build-A-Large-Language-Model-CN — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite