RRepoGEO

REPOGEO REPORT · LITE

lsdefine/simple_GRPO

Default branch main · commit 30f252ce · scanned 5/28/2026, 3:08:05 PM

GitHub: 1,680 stars · 132 forks

AI VISIBILITY SCORE
28 /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
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 lsdefine/simple_GRPO, 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 improve categorization

    Why:

    COPY-PASTE FIX
    llm, reinforcement-learning, grpo, deep-learning, pytorch, fine-tuning, memory-efficient, trl
  • highreadme#2
    Clarify the opening sentence of the README

    Why:

    CURRENT
    A very simple GRPO implement for reproducing r1-like LLM thinking.
    COPY-PASTE FIX
    A very simple **Reinforcement Learning (RL)** GRPO implementation for reproducing r1-like LLM thinking and **LLM fine-tuning**.
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/lsdefine/simple_GRPO

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 lsdefine/simple_GRPO
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pytorch/pytorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. pytorch/pytorch · recommended 2×
  2. microsoft/DeepSpeed · recommended 1×
  3. huggingface/accelerate · recommended 1×
  4. NVIDIA/Megatron-LM · recommended 1×
  5. Dao-AILab/flash-attention · recommended 1×
  • CATEGORY QUERY
    How to implement GRPO for large language models with memory-efficient training?
    you: not recommended
    AI recommended (in order):
    1. DeepSpeed (microsoft/DeepSpeed)
    2. PyTorch FSDP (pytorch/pytorch)
    3. Hugging Face Accelerate (huggingface/accelerate)
    4. Megatron-LM (NVIDIA/Megatron-LM)
    5. FlashAttention (Dao-AILab/flash-attention)
    6. Gradient Checkpointing (pytorch/pytorch)
    7. bitsandbytes (TimDettmers/bitsandbytes)

    AI recommended 7 alternatives but never named lsdefine/simple_GRPO. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a simple framework to experiment with RL algorithms like GRPO for LLM fine-tuning.
    you: not recommended
    AI recommended (in order):
    1. TRL (HuggingFace/trl)
    2. Hugging Face Transformers (huggingface/transformers)
    3. RLlib (ray-project/ray)
    4. Stable Baselines3 (DLR-RM/stable-baselines3)
    5. CleanRL (cleanrl/cleanrl)

    AI recommended 5 alternatives but never named lsdefine/simple_GRPO. 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 lsdefine/simple_GRPO?
    pass
    AI named lsdefine/simple_GRPO explicitly

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

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

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lsdefine/simple_GRPO — 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