REPOGEO REPORT · LITE

mesolitica/NLP-Models-Tensorflow

Default branch master · commit 0741216a · scanned 5/21/2026, 4:52:50 AM

GitHub: 1,780 stars · 714 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

22 /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

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 mesolitica/NLP-Models-Tensorflow, 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

Reposition the README's opening to highlight TensorFlow 1.x and Jupyter focus

Why:

CURRENT

NLP-Models-Tensorflow**, Gathers machine learning and tensorflow deep learning models for NLP problems, **code simplify inside Jupyter Notebooks 100%**.

COPY-PASTE FIX

NLP-Models-Tensorflow: A comprehensive collection of machine learning and deep learning models for NLP problems, specifically designed for **TensorFlow 1.x (1.13 < TF < 2.0)** and optimized for **100% simplified code within Jupyter Notebooks**.

mediumtopics#2

Add more specific topics to clarify the repository's focus

Why:

CURRENT

attention, chatbot, deep-learning, dnc-seq2seq, embedded, language-detection, lstm, lstm-seq2seq-tf, luong-api, machine-learning, neural-machine-translation, nlp, optical-character-recognition, pos-tagging, speech-to-text, summarization

COPY-PASTE FIX

attention, chatbot, deep-learning, dnc-seq2seq, embedded, language-detection, lstm, lstm-seq2seq-tf, luong-api, machine-learning, neural-machine-translation, nlp, optical-character-recognition, pos-tagging, speech-to-text, summarization, **tensorflow-1x, jupyter-notebooks, pre-trained-models, nlp-models-collection**

lowhomepage#3
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://github.com/mesolitica/NLP-Models-Tensorflow
```

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 mesolitica/NLP-Models-Tensorflow

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

TensorFlow Hub

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

TensorFlow Hub · recommended 2×
Hugging Face Transformers · recommended 2×
Google's Official BERT GitHub Repository · recommended 1×
TensorFlow Models GitHub Repository · recommended 1×
Keras Applications · recommended 1×

CATEGORY QUERY
Where can I find pre-trained deep learning models for common NLP tasks using TensorFlow 1.x?
you: not recommended
AI recommended (in order):
1. TensorFlow Hub
2. Hugging Face Transformers
3. Google's Official BERT GitHub Repository
4. TensorFlow Models GitHub Repository
5. Keras Applications
AI recommended 5 alternatives but never named mesolitica/NLP-Models-Tensorflow. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for easy-to-integrate TensorFlow deep learning models for natural language processing in notebooks.
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers
2. TensorFlow Hub
3. Keras NLP
4. spaCy
5. NLTK
AI recommended 5 alternatives but never named mesolitica/NLP-Models-Tensorflow. 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 mesolitica/NLP-Models-Tensorflow?
pass
AI did not name mesolitica/NLP-Models-Tensorflow — 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 mesolitica/NLP-Models-Tensorflow in production, what risks or prerequisites should they evaluate first?
pass
AI named mesolitica/NLP-Models-Tensorflow 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 mesolitica/NLP-Models-Tensorflow solve, and who is the primary audience?
pass
AI did not name mesolitica/NLP-Models-Tensorflow — 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?

Embed your GEO score

Drop this badge into the README of mesolitica/NLP-Models-Tensorflow. 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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HTML

<a href="https://repogeo.com/en/r/mesolitica/NLP-Models-Tensorflow"><img src="https://repogeo.com/badge/mesolitica/NLP-Models-Tensorflow.svg" alt="RepoGEO" /></a>

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mesolitica/NLP-Models-Tensorflow — 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