RRepoGEO

REPOGEO REPORT · LITE

DLLXW/baby-llama2-chinese

Default branch main · commit 98a20dbb · scanned 6/27/2026, 11:18:23 AM

GitHub: 2,926 stars · 356 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)

3 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 DLLXW/baby-llama2-chinese, 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

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

OVERALL DIRECTION
  • highreadme#1
    Clarify README's opening sentence to emphasize the provided solution

    Why:

    CURRENT
    本项目致力于构建一个小参数量的中文Llama2仓库。
    COPY-PASTE FIX
    本项目提供一个**完整的、可运行的中文Llama2小模型训练与微调流程**，旨在帮助用户在单张24G显卡上从头预训练并SFT得到一个具备简单中文问答能力的chat-llama2。
  • mediumhomepage#2
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    Add a URL to your project's official website or documentation portal in the repository settings.

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 DLLXW/baby-llama2-chinese
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. PyTorch · recommended 1×
  3. torchtext · recommended 1×
  4. jieba · recommended 1×
  5. TensorFlow · recommended 1×
  • CATEGORY QUERY
    How can I pre-train a small Chinese language model using a single GPU?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch
    3. torchtext
    4. jieba
    5. TensorFlow
    6. Keras
    7. Megatron-LM
    8. Fairseq

    AI recommended 8 alternatives but never named DLLXW/baby-llama2-chinese. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a complete open-source pipeline to build and fine-tune a custom Chinese LLM.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Accelerate
    3. DeepSpeed
    4. LoRA
    5. QLoRA
    6. peft
    7. FlashAttention-2
    8. bitsandbytes
    9. SentencePiece
    10. WandB

    AI recommended 10 alternatives but never named DLLXW/baby-llama2-chinese. 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 DLLXW/baby-llama2-chinese?
    pass
    AI did not name DLLXW/baby-llama2-chinese — 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 DLLXW/baby-llama2-chinese in production, what risks or prerequisites should they evaluate first?
    pass
    AI named DLLXW/baby-llama2-chinese 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 DLLXW/baby-llama2-chinese solve, and who is the primary audience?
    pass
    AI did not name DLLXW/baby-llama2-chinese — 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 DLLXW/baby-llama2-chinese. 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/DLLXW/baby-llama2-chinese.svg)](https://repogeo.com/en/r/DLLXW/baby-llama2-chinese)
HTML
<a href="https://repogeo.com/en/r/DLLXW/baby-llama2-chinese"><img src="https://repogeo.com/badge/DLLXW/baby-llama2-chinese.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

DLLXW/baby-llama2-chinese — 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