RRepoGEO

REPOGEO REPORT · LITE

conceptofmind/PaLM

Default branch main · commit c95d8c42 · scanned 6/13/2026, 1:17:39 PM

GitHub: 820 stars · 78 forks

AI VISIBILITY SCORE
35 /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
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 conceptofmind/PaLM, 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-model, llm, palm, google-palm, pytorch, deep-learning, machine-learning, nlp, generative-ai, open-source-llm
  • highhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://github.com/conceptofmind/PaLM
  • mediumreadme#3
    Strengthen the README's opening statement to clearly position the project

    Why:

    CURRENT
    # PaLM

## Acknowledgements
    COPY-PASTE FIX
    # PaLM
An open-source PyTorch implementation of Google's PaLM models, designed for researchers and developers to experiment with large language model architectures. This repository provides pre-trained models (150m, 410m, 1b, 2.1b, 3b) with 8k context length, trained on the C4 dataset, and compatible with Lucidrain's related projects.

## Acknowledgements

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 conceptofmind/PaLM
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. Llama 2 · recommended 1×
  3. Mistral 7B · recommended 1×
  4. Falcon · recommended 1×
  5. GPT-NeoX · recommended 1×
  • CATEGORY QUERY
    Where can I find an open-source implementation of a large language model for research?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Llama 2
    3. Mistral 7B
    4. Falcon
    5. GPT-NeoX
    6. OpenAssistant Conversations Dataset (OASST1)

    AI recommended 6 alternatives but never named conceptofmind/PaLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source models support a long context length for advanced natural language tasks?
    you: not recommended
    AI recommended (in order):
    1. Mistral Large
    2. Mixtral 8x22B
    3. Llama 3
    4. Qwen2
    5. Yi-34B-200K
    6. Gemma 2
    7. LongRoPE
    8. InternLM2-20B-LongContext

    AI recommended 8 alternatives but never named conceptofmind/PaLM. 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 conceptofmind/PaLM?
    pass
    AI named conceptofmind/PaLM explicitly

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

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

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

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conceptofmind/PaLM — 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