REPOGEO REPORT · LITE

neulab/prompt2model

Default branch main · commit d4cd23d5 · scanned 5/18/2026, 11:01:51 AM

GitHub: 2,015 stars · 182 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 neulab/prompt2model, 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 README opening to highlight specialized model generation and deployment

Why:

CURRENT

Prompt2Model is a system that takes a natural language task description (like the prompts used for LLMs such as ChatGPT) to train a small special-purpose model that is conducive for deployment.

COPY-PASTE FIX

Prompt2Model is a system designed to bridge the gap between natural language task descriptions (like those used for LLMs such as ChatGPT) and deployable, small special-purpose models. Unlike general LLMs or large ML platforms, Prompt2Model automates the creation of efficient, task-specific models directly from your prompts, making them ideal for production environments where cost, latency, and specialization are critical.

hightopics#2

Add specific topics to improve categorization

Why:

COPY-PASTE FIX

prompt-engineering, llm, machine-learning, model-generation, nlp, deployable-models, custom-models, fine-tuning, model-training, ai-tools

mediumhomepage#3
Add a project homepage URL
Why:
COPY-PASTE FIX
```
https://github.com/neulab/prompt2model
```

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 neulab/prompt2model

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Hugging Face AutoTrain Advanced

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Hugging Face AutoTrain Advanced · recommended 1×
huggingface/transformers · recommended 1×
Google Cloud AutoML Natural Language · recommended 1×
Azure Machine Learning · recommended 1×
Azure Cognitive Services for Language · recommended 1×

CATEGORY QUERY
How can I generate a deployable custom model from a natural language task description?
you: not recommended
AI recommended (in order):
1. Hugging Face AutoTrain Advanced
2. 🤗 Transformers (huggingface/transformers)
3. Google Cloud AutoML Natural Language
4. Azure Machine Learning
5. Azure Cognitive Services for Language
6. OpenAI API
7. GPT-3
8. GPT-4
9. Rasa (RasaHQ/rasa)
10. Ludwig (ludwig-ai/ludwig)
AI recommended 10 alternatives but never named neulab/prompt2model. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Tool to train small, efficient models directly from text prompts for specific tasks?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-3.5 Turbo / GPT-4
2. Hugging Face Transformers
3. SetFit
4. Ludwig
5. FastText
6. ONNX Runtime
AI recommended 6 alternatives but never named neulab/prompt2model. 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 neulab/prompt2model?
pass
AI named neulab/prompt2model explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts neulab/prompt2model in production, what risks or prerequisites should they evaluate first?
pass
AI named neulab/prompt2model 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 neulab/prompt2model solve, and who is the primary audience?
pass
AI named neulab/prompt2model 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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Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/neulab/prompt2model.svg)](https://repogeo.com/en/r/neulab/prompt2model)

HTML

<a href="https://repogeo.com/en/r/neulab/prompt2model"><img src="https://repogeo.com/badge/neulab/prompt2model.svg" alt="RepoGEO" /></a>

Pro

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neulab/prompt2model — 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