RRepoGEO

REPOGEO REPORT · LITE

michael-wzhu/Chinese-LlaMA2

Default branch main · commit 381465ea · scanned 6/7/2026, 6:53:06 AM

GitHub: 737 stars · 54 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 michael-wzhu/Chinese-LlaMA2, 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
    llama2, chinese-llm, large-language-model, nlp, deep-learning, fine-tuning, pre-training, open-source-llm, llm-adaptation, chinese-nlp
  • highreadme#2
    Strengthen the README's opening paragraph for immediate clarity

    Why:

    CURRENT
    就在不久前，Meta最新开源了Llama 2模型，完全可商用，看来Meta势必要与OpenAI (ClosedAI) 硬刚到底。虽然Llama 2对原版的LlaMA模型做了升级，但是其仍然对中文没有太好的支持，需要在中文上做定制化。所以我们决定在次开展Llama 2的中文汉化工作：
    COPY-PASTE FIX
    Chinese-LlaMA2 is a fully open-source and commercially viable adaptation of Meta's Llama 2 model, specifically optimized for robust Chinese language processing. Recognizing Llama 2's limited native Chinese support, this project provides comprehensive resources for pre-training, fine-tuning, and developing specialized Chinese LLMs.
  • mediumlicense#3
    Add a LICENSE file to clarify usage terms

    Why:

    COPY-PASTE FIX
    Add a `LICENSE` file to the repository root containing the full text of the Llama 2 Community License, as this project is an adaptation of Llama 2.

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 michael-wzhu/Chinese-LlaMA2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Qwen
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Qwen · recommended 1×
  2. Baichuan · recommended 1×
  3. ChatGLM · recommended 1×
  4. InternLM · recommended 1×
  5. Pangu-α · recommended 1×
  • CATEGORY QUERY
    Looking for an open-source large language model optimized for Chinese language processing.
    you: not recommended
    AI recommended (in order):
    1. Qwen
    2. Baichuan
    3. ChatGLM
    4. InternLM
    5. Pangu-α
    6. XVERSE

    AI recommended 6 alternatives but never named michael-wzhu/Chinese-LlaMA2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What commercially viable large language models offer robust performance in Chinese?
    you: not recommended
    AI recommended (in order):
    1. ERNIE Bot
    2. SenseChat
    3. Zhipu AI GLM
    4. Tencent Hunyuan
    5. Aliyun Tongyi Qianwen
    6. OpenAI GPT-4
    7. Meta Llama 3

    AI recommended 7 alternatives but never named michael-wzhu/Chinese-LlaMA2. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 michael-wzhu/Chinese-LlaMA2?
    pass
    AI named michael-wzhu/Chinese-LlaMA2 explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts michael-wzhu/Chinese-LlaMA2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named michael-wzhu/Chinese-LlaMA2 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 michael-wzhu/Chinese-LlaMA2 solve, and who is the primary audience?
    pass
    AI did not name michael-wzhu/Chinese-LlaMA2 — 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

Drop this badge into the README of michael-wzhu/Chinese-LlaMA2. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/michael-wzhu/Chinese-LlaMA2.svg)](https://repogeo.com/en/r/michael-wzhu/Chinese-LlaMA2)
HTML
<a href="https://repogeo.com/en/r/michael-wzhu/Chinese-LlaMA2"><img src="https://repogeo.com/badge/michael-wzhu/Chinese-LlaMA2.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

michael-wzhu/Chinese-LlaMA2 — 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