REPOGEO REPORT · LITE

Separius/awesome-sentence-embedding

Default branch master · commit 514c14af · scanned 5/10/2026, 8:07:45 PM

GitHub: 2,287 stars · 263 forks

AI VISIBILITY SCORE

28 /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

2 / 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 Separius/awesome-sentence-embedding, 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 README's opening to emphasize 'curated resource list' for discovery

Why:

CURRENT

A curated list of pretrained sentence and word embedding models

COPY-PASTE FIX

A comprehensive, curated list of pretrained sentence and word embedding models, designed as a resource for discovery and comparison, not a library or benchmark.

mediumhomepage#2
Add the repository URL as the homepage
Why:
COPY-PASTE FIX
```
https://github.com/Separius/awesome-sentence-embedding
```

lowtopics#3

Add 'nlp-resources' topic to reinforce resource type

Why:

CURRENT

awesome, awesome-list, bert, contextualized-representation, cross-lingual, embedding-models, language-model, natural-language, nlp, pretrained-embedding, pretrained-language-model, pretrained-models, sentence-embeddings, sentence-representations, subword-models, unsupervised-learning, word-embeddings, wordembedding

COPY-PASTE FIX

awesome, awesome-list, bert, contextualized-representation, cross-lingual, embedding-models, language-model, natural-language, nlp, nlp-resources, pretrained-embedding, pretrained-language-model, pretrained-models, sentence-embeddings, sentence-representations, subword-models, unsupervised-learning, word-embeddings, wordembedding

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 Separius/awesome-sentence-embedding

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

huggingface/transformers

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers · recommended 1×
UKPLab/sentence-transformers · recommended 1×
MTEB (Massive Text Embedding Benchmark) Leaderboard · recommended 1×
tensorflow/hub · recommended 1×
RaRe-Technologies/gensim · recommended 1×

CATEGORY QUERY
Where can I find a comprehensive list of pretrained sentence embedding models for NLP?
you: not recommended
AI recommended (in order):
1. Hugging Face Models (Transformers library) (huggingface/transformers)
2. Sentence-Transformers Documentation (UKPLab/sentence-transformers)
3. MTEB (Massive Text Embedding Benchmark) Leaderboard
4. TensorFlow Hub (tensorflow/hub)
5. Gensim (Word2Vec/Doc2Vec) (RaRe-Technologies/gensim)
AI recommended 5 alternatives but never named Separius/awesome-sentence-embedding. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best resources for comparing various word and sentence embedding techniques?
you: not recommended
AI recommended (in order):
1. Papers With Code
2. Sentence-BERT (SBERT)
3. Hugging Face Transformers Library
4. MTEB (embeddings-benchmark/mteb)
5. Gensim
6. TensorFlow Hub
7. PyTorch Hub
AI recommended 7 alternatives but never named Separius/awesome-sentence-embedding. 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 Separius/awesome-sentence-embedding?
pass
AI did not name Separius/awesome-sentence-embedding — 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 Separius/awesome-sentence-embedding in production, what risks or prerequisites should they evaluate first?
pass
AI named Separius/awesome-sentence-embedding 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 Separius/awesome-sentence-embedding solve, and who is the primary audience?
pass
AI named Separius/awesome-sentence-embedding 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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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/Separius/awesome-sentence-embedding.svg)](https://repogeo.com/en/r/Separius/awesome-sentence-embedding)

HTML

<a href="https://repogeo.com/en/r/Separius/awesome-sentence-embedding"><img src="https://repogeo.com/badge/Separius/awesome-sentence-embedding.svg" alt="RepoGEO" /></a>

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite