RRepoGEO

REPOGEO REPORT · LITE

920232796/bert_seq2seq

Default branch master · commit c7988b01 · scanned 5/27/2026, 5:03:44 AM

GitHub: 1,306 stars · 208 forks

AI VISIBILITY SCORE
28 /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
2 / 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 920232796/bert_seq2seq, 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
    Clarify repo status and relationship to `bert_seq2seq_DDP` in README

    Why:

    CURRENT
    目前重构了一版分布式训练的版本，**改下参数即可直接进行多GPU的训练**，而**不需要额外的命令，不需要添加额外的代码**！欢迎前往https://github.com/920232796/bert_seq2seq_DDP 详细了解
    COPY-PASTE FIX
    **重要提示：** 本仓库 `bert_seq2seq` 是原始版本，目前已不再积极维护。我们已将分布式训练等最新功能迁移至新仓库 `bert_seq2seq_DDP`。如果您正在寻找最新、最活跃的版本，请前往 [https://github.com/920232796/bert_seq2seq_DDP](https://github.com/920232796/bert_seq2seq_DDP) 获取详细信息和最新代码。
  • highreadme#2
    Reposition README H1 to clearly state purpose and audience

    Why:

    CURRENT
    # bert_seq2seq
    COPY-PASTE FIX
    # bert_seq2seq: 轻量级PyTorch框架，用于BERT/GPT2/T5等模型实现多种NLP任务 (如Seq2Seq, 文本分类, NER)
  • mediumabout#3
    Add homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/920232796/bert_seq2seq_DDP

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 920232796/bert_seq2seq
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-Lightning · recommended 1×
  3. spaCy · recommended 1×
  4. AllenNLP · recommended 1×
  5. fairseq · recommended 1×
  • CATEGORY QUERY
    What are good PyTorch libraries for various NLP tasks like text classification and sequence generation?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch-Lightning
    3. spaCy
    4. AllenNLP
    5. fairseq
    6. torchtext

    AI recommended 6 alternatives but never named 920232796/bert_seq2seq. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch framework for abstractive summarization and named entity recognition with distributed training.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. PyTorch Lightning (Lightning-AI/lightning)
    3. Fairseq (facebookresearch/fairseq)
    4. DeepSpeed (microsoft/DeepSpeed)
    5. Accelerate (huggingface/accelerate)

    AI recommended 5 alternatives but never named 920232796/bert_seq2seq. 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 920232796/bert_seq2seq?
    pass
    AI named 920232796/bert_seq2seq explicitly

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

  • If a team adopts 920232796/bert_seq2seq in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 920232796/bert_seq2seq 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 920232796/bert_seq2seq solve, and who is the primary audience?
    pass
    AI did not name 920232796/bert_seq2seq — 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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