RRepoGEO

REPOGEO REPORT · LITE

mbzuai-nlp/LaMini-LM

Default branch main · commit 48cfa492 · scanned 6/14/2026, 4:57:56 AM

GitHub: 822 stars · 50 forks

AI VISIBILITY SCORE
30 /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
3 / 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 mbzuai-nlp/LaMini-LM, 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
  • highlicense#1
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Add the following topics: large-language-models, llm, instruction-following, model-distillation, efficient-llm, small-llm, nlp, deep-learning.
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    Set the homepage URL to the project's paper link: https://arxiv.org/abs/2304.14402 or a dedicated project page if one exists.

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 mbzuai-nlp/LaMini-LM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mistral 7B Instruct v0.2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Mistral 7B Instruct v0.2 · recommended 2×
  2. Llama 3 8B Instruct · recommended 2×
  3. Phi-3-mini-4k-instruct · recommended 2×
  4. Gemma 2B/7B Instruct · recommended 1×
  5. TinyLlama 1.1B · recommended 1×
  • CATEGORY QUERY
    What are some efficient, compact large language models for resource-constrained applications?
    you: not recommended
    AI recommended (in order):
    1. Mistral 7B Instruct v0.2
    2. Llama 3 8B Instruct
    3. Gemma 2B/7B Instruct
    4. Phi-3-mini-4k-instruct
    5. TinyLlama 1.1B
    6. OpenHermes 2.5 Mistral 7B

    AI recommended 6 alternatives but never named mbzuai-nlp/LaMini-LM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking small language models that excel at instruction following, suitable for faster inference.
    you: not recommended
    AI recommended (in order):
    1. Mistral 7B Instruct v0.2
    2. Llama 3 8B Instruct
    3. Gemma 7B Instruct
    4. Phi-3-mini-4k-instruct
    5. Qwen1.5-7B-Chat
    6. Zephyr-7B-beta

    AI recommended 6 alternatives but never named mbzuai-nlp/LaMini-LM. 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 mbzuai-nlp/LaMini-LM?
    pass
    AI named mbzuai-nlp/LaMini-LM explicitly

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

  • If a team adopts mbzuai-nlp/LaMini-LM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mbzuai-nlp/LaMini-LM 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 mbzuai-nlp/LaMini-LM solve, and who is the primary audience?
    pass
    AI named mbzuai-nlp/LaMini-LM explicitly

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

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mbzuai-nlp/LaMini-LM — 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