RRepoGEO

REPOGEO REPORT · LITE

huawei-noah/Pretrained-Language-Model

Default branch master · commit 0598f02d · scanned 6/24/2026, 6:27:34 PM

GitHub: 3,163 stars · 641 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 huawei-noah/Pretrained-Language-Model, 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 the README's opening sentence to highlight key strengths

    Why:

    CURRENT
    This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei Noah's Ark Lab.
    COPY-PASTE FIX
    This repository provides state-of-the-art pretrained language models, with a strong focus on **efficiency, compression techniques (e.g., TinyBERT, TernaryBERT), and high-performing models for Chinese natural language processing (e.g., PanGu-α, NEZHA)**, all developed by Huawei Noah's Ark Lab.
  • highlicense#2
    Add a standard open-source license file

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the Apache License 2.0. (The full text of the Apache License 2.0 can be found at https://www.apache.org/licenses/LICENSE-2.0.txt)
  • mediumhomepage#3
    Add the official Huawei Noah's Ark Lab homepage URL

    Why:

    COPY-PASTE FIX
    Set the repository homepage URL to `https://www.huawei.com/en/research/noahs-ark-lab` in the repository settings.

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 huawei-noah/Pretrained-Language-Model
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 3×
  2. huggingface/optimum · recommended 2×
  3. microsoft/onnxruntime · recommended 2×
  4. NVIDIA/TensorRT · recommended 2×
  5. pytorch/pytorch · recommended 2×
  • CATEGORY QUERY
    How to reduce the size and improve inference speed of large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Optimum (huggingface/optimum)
    2. ONNX Runtime (microsoft/onnxruntime)
    3. NVIDIA TensorRT (NVIDIA/TensorRT)
    4. Hugging Face Optimum (huggingface/optimum)
    5. PyTorch (pytorch/pytorch)
    6. TensorFlow Model Optimization Toolkit (tensorflow/model-optimization)
    7. Hugging Face Transformers (huggingface/transformers)
    8. PyTorch (pytorch/pytorch)
    9. TensorFlow (tensorflow/tensorflow)
    10. MobileNet
    11. EfficientNet
    12. DeBERTa-v3 (microsoft/DeBERTa)
    13. Llama.cpp (ggerganov/llama.cpp)
    14. NVIDIA TensorRT (NVIDIA/TensorRT)
    15. ONNX Runtime (microsoft/onnxruntime)
    16. OpenVINO Toolkit (openvinotoolkit/openvino)
    17. DeepSpeed (microsoft/DeepSpeed)
    18. Hugging Face Transformers (huggingface/transformers)
    19. Medusa (FasterDecoding/Medusa)
    20. xFormers (facebookresearch/xformers)
    21. Hugging Face Transformers (huggingface/transformers)

    AI recommended 21 alternatives but never named huawei-noah/Pretrained-Language-Model. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking efficient pretrained language models for Chinese natural language processing tasks.
    you: not recommended
    AI recommended (in order):
    1. BERT (Bidirectional Encoder Representations from Transformers) - Chinese
    2. RoBERTa (A Robustly Optimized BERT Pretraining Approach) - Chinese
    3. ERNIE (Enhanced Representation from kNowledge IntEgration) - Chinese
    4. MacBERT (Masked Language Model as a Confident Token-level Predictor) - Chinese
    5. ELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) - Chinese
    6. XLNet (Generalized Autoregressive Pretraining for Language Understanding) - Chinese
    7. mT5 (Multilingual T5) - Chinese

    AI recommended 7 alternatives but never named huawei-noah/Pretrained-Language-Model. 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 huawei-noah/Pretrained-Language-Model?
    pass
    AI named huawei-noah/Pretrained-Language-Model explicitly

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

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