RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/lingua

Default branch main · commit 437d680e · scanned 5/17/2026, 6:17:59 PM

GitHub: 4,760 stars · 270 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 facebookresearch/lingua, 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
    llm, large-language-models, pytorch, deep-learning, machine-learning, research, training, inference
  • mediumreadme#2
    Clarify the README's opening sentence to emphasize general LLM research

    Why:

    CURRENT
    Meta Lingua is a minimal and fast LLM training and inference library designed for research.
    COPY-PASTE FIX
    Meta Lingua is a minimal and fast LLM training and inference library designed for general LLM research, focusing on easy-to-modify PyTorch components for new architectures, losses, and data.
  • lowreadme#3
    Add an explicit "Examples" section to the README

    Why:

    COPY-PASTE FIX
    ## Examples

Explore how to use Meta Lingua through our provided applications in the `apps/` directory. Each app showcases different aspects of LLM training, inference, and evaluation.

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 facebookresearch/lingua
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 1×
  2. Hugging Face Transformers · recommended 1×
  3. PyTorch Lightning · recommended 1×
  4. DeepSpeed · recommended 1×
  5. xFormers · recommended 1×
  • CATEGORY QUERY
    What are some flexible PyTorch libraries for experimenting with new LLM architectures?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. Hugging Face Transformers
    3. PyTorch Lightning
    4. DeepSpeed
    5. xFormers
    6. Trax

    AI recommended 6 alternatives but never named facebookresearch/lingua. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a minimal and fast codebase for custom large language model training and inference.
    you: not recommended
    AI recommended (in order):
    1. nanoGPT (karpathy/nanoGPT)
    2. LitGPT (Lightning-AI/litgpt)
    3. Hugging Face Transformers (huggingface/transformers)
    4. torch.compile
    5. xformers (facebookresearch/xformers)
    6. DeepSpeed (microsoft/DeepSpeed)
    7. llama.cpp (ggerganov/llama.cpp)

    AI recommended 7 alternatives but never named facebookresearch/lingua. 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 facebookresearch/lingua?
    pass
    AI named facebookresearch/lingua explicitly

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

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

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

Embed your GEO score

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facebookresearch/lingua — 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
facebookresearch/lingua — RepoGEO report