RRepoGEO

REPOGEO REPORT · LITE

neulab/prompt2model

Default branch main · commit d4cd23d5 · scanned 6/29/2026, 5:07:18 PM

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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    machine-learning, nlp, model-generation, prompt-engineering, deployable-ai, custom-ml-models, llm-alternatives, ai-tools
  • highreadme#2
    Clarify the unique value proposition in the README's opening paragraph

    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 instructions (like those for LLMs) and deployable, *specialized small models*. Unlike large language models, `Prompt2Model` generates compact, efficient models tailored for specific tasks, making them ideal for production deployment where efficiency and cost are critical.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://neulab.github.io/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
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-3.5 / GPT-4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-3.5 / GPT-4 · recommended 1×
  2. Claude · recommended 1×
  3. Llama 2 · recommended 1×
  4. OpenAI Fine-tuning · recommended 1×
  5. huggingface/autotrain-advanced · recommended 1×
  • CATEGORY QUERY
    How to train a custom machine learning model using only natural language prompts?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-3.5 / GPT-4
    2. Claude
    3. Llama 2
    4. OpenAI Fine-tuning
    5. Hugging Face AutoTrain Advanced (huggingface/autotrain-advanced)
    6. Google Cloud Vertex AI
    7. Microsoft Azure Machine Learning
    8. Vellum
    9. Dust.tt
    10. LangChain (langchain-ai/langchain)

    AI recommended 10 alternatives but never named neulab/prompt2model. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool to create deployable, smaller models from text instructions instead of large LLMs.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. OpenVINO Toolkit (openvinotoolkit/openvino)
    3. ONNX Runtime (microsoft/onnxruntime)
    4. TensorFlow Lite (tensorflow/tensorflow)
    5. PyTorch Mobile (pytorch/pytorch)
    6. MLflow (mlflow/mlflow)
    7. BentoML (bentoml/bentoml)

    AI recommended 7 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?

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite