RRepoGEO

REPOGEO REPORT · LITE

tensorflow/nmt

Default branch master · commit 0be86425 · scanned 5/19/2026, 8:17:53 AM

GitHub: 6,464 stars · 1,936 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 tensorflow/nmt, 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
    neural-machine-translation, nmt, seq2seq, sequence-to-sequence, attention-mechanism, deep-learning, tensorflow, tutorial, reference-implementation
  • mediumreadme#2
    Add a concise introductory sentence to the README

    Why:

    COPY-PASTE FIX
    Add this sentence immediately after the H1: "This repository provides a comprehensive, step-by-step tutorial and reference implementation for building Neural Machine Translation (NMT) systems from scratch using TensorFlow, including sequence-to-sequence models with attention."
  • lowabout#3
    Expand the repository's "About" description

    Why:

    CURRENT
    TensorFlow Neural Machine Translation Tutorial
    COPY-PASTE FIX
    A comprehensive TensorFlow tutorial and reference implementation for building Neural Machine Translation (NMT) systems from scratch, including sequence-to-sequence models with attention.

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 tensorflow/nmt
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. TensorFlow · recommended 2×
  3. Keras · recommended 2×
  4. Opus · recommended 1×
  5. Moses · recommended 1×
  • CATEGORY QUERY
    How to build a neural machine translation system from scratch using deep learning?
    you: not recommended
    AI recommended (in order):
    1. Opus
    2. Moses
    3. SentencePiece
    4. Hugging Face `tokenizers`
    5. PyTorch
    6. TensorFlow
    7. JAX
    8. PyTorch Lightning
    9. Keras
    10. sacreBLEU
    11. Hugging Face `evaluate`
    12. Hugging Face `transformers`

    AI recommended 12 alternatives but never named tensorflow/nmt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tutorial to implement sequence-to-sequence models with attention in a deep learning framework.
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. Keras
    4. Hugging Face Transformers Library
    5. Analytics Vidhya
    6. Towards Data Science

    AI recommended 6 alternatives but never named tensorflow/nmt. 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 tensorflow/nmt?
    pass
    AI named tensorflow/nmt explicitly

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

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

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

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tensorflow/nmt — 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