RRepoGEO

REPOGEO REPORT · LITE

pytorch/text

Default branch main · commit a5e61063 · scanned 6/23/2026, 7:57:45 PM

GitHub: 3,562 stars · 809 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
77 /100
Needs work
Category recall
2 / 2
Avg rank #6.0 when recommended
Rule findings
2 pass · 0 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 pytorch/text, 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
  • highabout#1
    Update the repository description to reflect end-of-life status

    Why:

    CURRENT
    Models, data loaders and abstractions for language processing, powered by PyTorch
    COPY-PASTE FIX
    Legacy library: Models, data loaders and abstractions for language processing, powered by PyTorch. Development has stopped; 0.18 (April 2024) is the last stable release.
  • mediumreadme#2
    Add a concise introductory sentence to the README

    Why:

    COPY-PASTE FIX
    Add the following sentence at the very beginning of the README, before the 'WARNING' section: 'TorchText provides essential tools for text processing and deep learning with PyTorch, including datasets, data loaders, and pre-trained models.'
  • mediumtopics#3
    Add more specific NLP-related topics

    Why:

    CURRENT
    data-loader, dataset, deep-learning, models, nlp, pytorch
    COPY-PASTE FIX
    data-loader, dataset, deep-learning, models, nlp, pytorch, tokenization, text-processing, embeddings, sequence-modeling, text-classification

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
2 / 2
100% of queries surface pytorch/text
Avg rank
#6.0
Lower is better. #1 = top recommendation.
Share of voice
11%
Of all named tools, what % are you?
Top rival
apache/arrow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. apache/arrow · recommended 2×
  2. huggingface/transformers · recommended 2×
  3. explosion/spaCy · recommended 2×
  4. nltk/nltk · recommended 2×
  5. huggingface/datasets · recommended 1×
  • CATEGORY QUERY
    How can I efficiently load and preprocess text datasets for deep learning models in PyTorch?
    you: #8
    AI recommended (in order):
    1. Hugging Face Datasets (huggingface/datasets)
    2. Apache Arrow (apache/arrow)
    3. Hugging Face Transformers (huggingface/transformers)
    4. torch.utils.data.Dataset
    5. torch.utils.data.DataLoader
    6. spaCy (explosion/spaCy)
    7. NLTK (nltk/nltk)
    8. torchtext (pytorch/text) ← you
    9. Pandas (pandas-dev/pandas)
    10. Dask (dask/dask)
    11. Parquet (apache/parquet-format)
    12. pyarrow (apache/arrow)
    Show full AI answer
  • CATEGORY QUERY
    What Python libraries offer pre-trained NLP models and text processing utilities for deep learning?
    you: #4
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. spaCy (explosion/spaCy)
    3. NLTK (nltk/nltk)
    4. TorchText (pytorch/text) ← you
    5. Keras (keras-team/keras)
    6. Gensim (piskvorky/gensim)
    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 pytorch/text?
    pass
    AI named pytorch/text explicitly

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

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

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

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pytorch/text — 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