RRepoGEO

REPOGEO REPORT · LITE

LaurentMazare/tch-rs

Default branch main · commit bbf49e6d · scanned 6/25/2026, 4:57:25 AM

GitHub: 5,431 stars · 438 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)

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

AI VISIBILITY SCORE
84 /100
Healthy
Category recall
2 / 2
Avg rank #2.0 when recommended
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 LaurentMazare/tch-rs, 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
  • highhomepage#1
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://docs.rs/tch
  • mediumreadme#2
    Add a 'Comparison with other Rust ML frameworks' section to README

    Why:

    COPY-PASTE FIX
    ## Comparison with other Rust ML frameworks

[Consider adding a section here that compares tch-rs to native Rust ML frameworks like burn, dfdx, and candle, emphasizing tch-rs's direct access to the PyTorch C++ API (LibTorch) and its extensive operator set, while noting the trade-offs.]
  • lowreadme#3
    Populate or link to a changelog in the README

    Why:

    CURRENT
    changelog
    COPY-PASTE FIX
    ## Changelog

[Either populate this section with recent changes or link to a dedicated CHANGELOG.md file or GitHub Releases page.]

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
2 / 2
100% of queries surface LaurentMazare/tch-rs
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
11%
Of all named tools, what % are you?
Top rival
burn
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. burn · recommended 1×
  2. dfdx · recommended 1×
  3. candle · recommended 1×
  4. RustNN · recommended 1×
  5. PyTorch · recommended 1×
  • CATEGORY QUERY
    How can I perform deep learning tasks using a neural network library in Rust?
    you: #1
    AI recommended (in order):
    1. tch-rs ← you
    2. burn
    3. dfdx
    4. candle
    5. RustNN
    Show full AI answer
  • CATEGORY QUERY
    What are the options for integrating a robust machine learning framework with Rust applications?
    you: #3
    AI recommended (in order):
    1. PyTorch
    2. TorchGeo
    3. tch-rs (LaurentMazare/tch-rs) ← you
    4. TensorFlow
    5. rust-tf (tensorflow/rust)
    6. tensorflow-rust
    7. ONNX Runtime
    8. onnxruntime-rs (nbigaouette/onnxruntime-rs)
    9. LightGBM
    10. lightgbm-rs (rust-ml/lightgbm-rs)
    11. XGBoost
    12. xgboost-rs (davechallis/xgboost-rs)
    13. tract (sonos/tract)
    14. linfa (rust-ml/linfa)
    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 LaurentMazare/tch-rs?
    pass
    AI named LaurentMazare/tch-rs explicitly

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

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

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

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LaurentMazare/tch-rs — 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