RRepoGEO

REPOGEO REPORT · LITE

lucidrains/reformer-pytorch

Default branch master · commit 66a19b6c · scanned 5/13/2026, 10:57:09 AM

GitHub: 2,191 stars · 252 forks

AI VISIBILITY SCORE
53 /100
Needs work
Category recall
1 / 2
Avg rank #2.0 when recommended
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 lucidrains/reformer-pytorch, 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
  • highreadme#1
    Strengthen README's opening sentence to highlight long sequence efficiency

    Why:

    CURRENT
    This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB
    COPY-PASTE FIX
    This repository provides a clean PyTorch implementation of the Reformer model, specifically designed to address the high memory and computational costs of standard Transformers when processing very long sequences.
  • mediumtopics#2
    Add topics related to long sequence processing and memory efficiency

    Why:

    CURRENT
    artificial-intelligence, attention-mechanism, machine-learning, pytorch, transformers
    COPY-PASTE FIX
    artificial-intelligence, attention-mechanism, machine-learning, pytorch, transformers, long-sequences, memory-efficient, deep-learning-models
  • mediumhomepage#3
    Add the Reformer paper link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://openreview.net/pdf?id=rkgNKkHtvB

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
1 / 2
50% of queries surface lucidrains/reformer-pytorch
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
10%
Of all named tools, what % are you?
Top rival
FlashAttention
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. FlashAttention · recommended 1×
  2. xformers · recommended 1×
  3. Longformer · recommended 1×
  4. BigBird · recommended 1×
  5. Performer · recommended 1×
  • CATEGORY QUERY
    How to implement an efficient Transformer model for very long sequences in PyTorch?
    you: not recommended
    AI recommended (in order):
    1. FlashAttention
    2. xformers
    3. Longformer
    4. BigBird
    5. Performer
    6. Reformer

    AI recommended 6 alternatives but never named lucidrains/reformer-pytorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a PyTorch library to build memory-efficient transformer models with LSH attention.
    you: #2
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. Reformer-pytorch (lucidrains/reformer-pytorch) ← you
    3. DeepSpeed (microsoft/DeepSpeed)
    4. FairScale (facebookresearch/fairscale)
    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 lucidrains/reformer-pytorch?
    pass
    AI did not name lucidrains/reformer-pytorch — 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 lucidrains/reformer-pytorch in production, what risks or prerequisites should they evaluate first?
    pass
    AI named lucidrains/reformer-pytorch 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 lucidrains/reformer-pytorch solve, and who is the primary audience?
    pass
    AI did not name lucidrains/reformer-pytorch — 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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