RRepoGEO

REPOGEO REPORT · LITE

huggingface/pytorch-openai-transformer-lm

Default branch master · commit bfd8e098 · scanned 5/23/2026, 6:52:59 PM

GitHub: 1,522 stars · 283 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 huggingface/pytorch-openai-transformer-lm, 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 H1 and opening paragraph to clarify historical context

    Why:

    CURRENT
    # PyTorch implementation of OpenAI's Finetuned Transformer Language Model

This is a PyTorch implementation of the TensorFlow code provided with OpenAI's paper "Improving Language Understanding by Generative Pre-Training" by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.
    COPY-PASTE FIX
    # PyTorch implementation of OpenAI's Original Transformer Language Model (GPT-1)

This repository provides a PyTorch implementation of the *original* OpenAI Transformer Language Model (often referred to as GPT-1), based on the TensorFlow code from their 2018 paper "Improving Language Understanding by Generative Pre-Training". It includes a script to load the weights pre-trained by OpenAI for this specific, foundational model, distinct from the broader Hugging Face `transformers` library.
  • mediumtopics#2
    Add more specific topics to clarify historical context

    Why:

    CURRENT
    language-model, neural-networks, openai, pytorch, transformer
    COPY-PASTE FIX
    language-model, neural-networks, openai, pytorch, transformer, gpt-1, legacy, historical-implementation, nlp-research
  • lowhomepage#3
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://s3-us-west-2.amazonaws.com/openai-assets/research-papers/language-unsupervised/language_understanding_paper.pdf

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 huggingface/pytorch-openai-transformer-lm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. PyTorch · recommended 1×
  3. PyTorch Lightning · recommended 1×
  4. Accelerate · recommended 1×
  5. DeepSpeed · recommended 1×
  • CATEGORY QUERY
    How to implement a transformer language model for generative pre-training in PyTorch?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch
    3. PyTorch Lightning
    4. Accelerate
    5. DeepSpeed

    AI recommended 5 alternatives but never named huggingface/pytorch-openai-transformer-lm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find pre-trained transformer language models compatible with PyTorch for fine-tuning?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers library
    2. PyTorch Hub
    3. Fairseq
    4. TorchText
    5. TensorFlow Hub

    AI recommended 5 alternatives but never named huggingface/pytorch-openai-transformer-lm. 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 huggingface/pytorch-openai-transformer-lm?
    pass
    AI did not name huggingface/pytorch-openai-transformer-lm — 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 huggingface/pytorch-openai-transformer-lm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named huggingface/pytorch-openai-transformer-lm 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 huggingface/pytorch-openai-transformer-lm solve, and who is the primary audience?
    pass
    AI did not name huggingface/pytorch-openai-transformer-lm — 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?

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  • Brand-free category queries5 vs 2 in Lite
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