RRepoGEO

REPOGEO REPORT · LITE

OpenBMB/BMTrain

Default branch main · commit 30e64697 · scanned 6/12/2026, 6:42:06 PM

GitHub: 624 stars · 88 forks

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 OpenBMB/BMTrain, 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
    deep-learning, distributed-training, large-models, llm, model-training, pytorch, gpu-acceleration, memory-optimization, finetuning, pretraining
  • mediumhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://bmtrain.readthedocs.io/en/latest/
  • lowreadme#3
    Strengthen the README's opening statement

    Why:

    CURRENT
    BMTrain is an efficient large model training toolkit that can be used to train large models with tens of billions of parameters.
    COPY-PASTE FIX
    BMTrain is a unified and flexible framework for efficient large model training, simplifying distributed computing and memory management for models with tens of billions of parameters.

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 OpenBMB/BMTrain
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Accelerate
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Accelerate · recommended 2×
  2. DeepSpeed · recommended 2×
  3. PyTorch FSDP · recommended 2×
  4. Hugging Face Transformers · recommended 1×
  5. NVIDIA NeMo Framework · recommended 1×
  • CATEGORY QUERY
    How can I efficiently train and fine-tune very large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Hugging Face Accelerate
    3. DeepSpeed
    4. PyTorch FSDP
    5. NVIDIA NeMo Framework
    6. Colossal-AI
    7. JAX
    8. Flax
    9. Google Cloud TPUs
    10. Hugging Face PEFT

    AI recommended 10 alternatives but never named OpenBMB/BMTrain. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help with distributed training and memory optimization for massive deep learning models?
    you: not recommended
    AI recommended (in order):
    1. PyTorch FSDP
    2. DeepSpeed
    3. Megatron-LM
    4. Hugging Face Accelerate
    5. TensorFlow Distributed Strategy API
    6. Horovod
    7. FairScale

    AI recommended 7 alternatives but never named OpenBMB/BMTrain. 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 OpenBMB/BMTrain?
    pass
    AI named OpenBMB/BMTrain explicitly

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

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

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

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OpenBMB/BMTrain — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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