RRepoGEO

REPOGEO REPORT · LITE

hiyouga/FastEdit

Default branch main · commit 76a8cf62 · scanned 6/21/2026, 10:21:43 PM

GitHub: 1,366 stars · 104 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)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 hiyouga/FastEdit, 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
    Clarify FastEdit's role as an LLM editing library in the README's opening.

    Why:

    CURRENT
    # FastEdit ⚡🩹
*Editing large language models within 10 seconds*
    COPY-PASTE FIX
    # FastEdit ⚡🩹: An Efficient Library for LLM Factual Editing
*A Python library for editing large language models within 10 seconds, implementing state-of-the-art methods like ROME.*
  • hightopics#2
    Add specific LLM editing method names and categories to topics.

    Why:

    CURRENT
    bloom, chatbots, chatgpt, falcon, gpt, large-language-models, llama, llms, pytorch, transformers
    COPY-PASTE FIX
    bloom, chatbots, chatgpt, falcon, gpt, large-language-models, llama, llms, pytorch, transformers, llm-editing, model-editing, knowledge-editing, factual-editing, rome-algorithm
  • mediumhomepage#3
    Add a homepage URL to the repository metadata.

    Why:

    COPY-PASTE FIX
    https://github.com/hiyouga/FastEdit

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 hiyouga/FastEdit
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LoRA
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LoRA · recommended 2×
  2. QLoRA · recommended 2×
  3. ROME · recommended 2×
  4. MEND · recommended 2×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    How to efficiently update or inject new factual knowledge into a large language model?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Hugging Face Transformers
    5. LoRA
    6. QLoRA
    7. ROME
    8. MEND
    9. MEMIT

    AI recommended 9 alternatives but never named hiyouga/FastEdit. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are fast methods for editing specific factual information in pre-trained LLMs?
    you: not recommended
    AI recommended (in order):
    1. ROME
    2. MEND
    3. SERAC
    4. KNIFE
    5. LEACE
    6. LoRA
    7. QLoRA
    8. Knowledge Neurons

    AI recommended 8 alternatives but never named hiyouga/FastEdit. 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 hiyouga/FastEdit?
    pass
    AI named hiyouga/FastEdit explicitly

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

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

    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 hiyouga/FastEdit. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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hiyouga/FastEdit — 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
hiyouga/FastEdit — RepoGEO report