RRepoGEO

REPOGEO REPORT · LITE

Om-Alve/smolGPT

Default branch main · commit 001f9c1a · scanned 5/14/2026, 4:08:21 AM

GitHub: 1,471 stars · 125 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 Om-Alve/smolGPT, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise description to the repository's About section

    Why:

    COPY-PASTE FIX
    A minimal PyTorch implementation for training small LLMs from scratch, designed for educational purposes and simplicity, featuring efficient training, flash attention, and modern sampling techniques.
  • mediumreadme#2
    Add a 'Why smolGPT?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why smolGPT? 🤔

While other excellent LLM implementations exist, smolGPT stands out for its **extreme minimalism and educational focus**. It provides a bare-bones, from-scratch implementation of a GPT model to illustrate its fundamental architecture and workings, prioritizing clarity and hackability over production readiness or extensive feature sets. It's ideal for learning and experimenting with modern LLM concepts.

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 Om-Alve/smolGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pytorch/pytorch
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. pytorch/pytorch · recommended 3×
  2. huggingface/datasets · recommended 1×
  3. google/sentencepiece · recommended 1×
  4. huggingface/tokenizers · recommended 1×
  5. arogozhnikov/einops · recommended 1×
  • CATEGORY QUERY
    How to train a small custom large language model from scratch using PyTorch?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Datasets (huggingface/datasets)
    2. SentencePiece (google/sentencepiece)
    3. Hugging Face Tokenizers (huggingface/tokenizers)
    4. PyTorch (pytorch/pytorch)
    5. einops (arogozhnikov/einops)
    6. FlashAttention (Dao-AILab/flash-attention)
    7. PyTorch Lightning (Lightning-AI/lightning)
    8. Accelerate (huggingface/accelerate)
    9. AdamW (pytorch/pytorch)
    10. torch.cuda.amp.autocast (pytorch/pytorch)
    11. Weights & Biases (wandb/wandb)
    12. TensorBoard (tensorflow/tensorboard)

    AI recommended 12 alternatives but never named Om-Alve/smolGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a minimal PyTorch LLM implementation with flash attention and modern sampling techniques.
    you: not recommended
    AI recommended (in order):
    1. nanoGPT
    2. Lit-GPT
    3. minGPT
    4. Hugging Face `transformers` library
    5. `xformers` library

    AI recommended 5 alternatives but never named Om-Alve/smolGPT. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 Om-Alve/smolGPT?
    pass
    AI named Om-Alve/smolGPT explicitly

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

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

    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 Om-Alve/smolGPT. 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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Om-Alve/smolGPT — 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