REPOGEO REPORT · LITE

huawei-noah/Pretrained-Language-Model

Default branch master · commit 0598f02d · scanned 5/14/2026, 6:12:40 AM

GitHub: 3,162 stars · 642 forks

AI VISIBILITY SCORE

15 /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

0 / 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 paragraph to emphasize Chinese NLP and optimization

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 Chinese language models (such as PanGu-α and NEZHA) and advanced optimization techniques (like TinyBERT, DynaBERT, TernaryBERT) developed by Huawei Noah's Ark Lab. It focuses on large-scale models and efficient deployment for Chinese NLP tasks.

highlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root containing the full text of the Apache-2.0 license.

mediumhomepage#3

Add a homepage URL to the repository's About section

Why:

COPY-PASTE FIX

Add a relevant URL (e.g., to the Huawei Noah's Ark Lab or a dedicated project page) in the repository's 'About' section as its homepage.

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

Of all named tools, what % are you?

Top rival

huggingface/transformers

Recommended in 3 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers · recommended 3×
huggingface/optimum · recommended 2×
NVIDIA TensorRT · recommended 2×
openvinotoolkit/openvino · recommended 2×
microsoft/onnxruntime · recommended 2×

CATEGORY QUERY
Looking for robust pretrained language models for Chinese NLP tasks, including large-scale options.
you: not recommended
AI recommended (in order):
1. ERNIE 3.0 Titan
2. CPM-2
3. Pangu-α
4. BERT-wwm-ext
5. MacBERT
6. RoBERTa-wwm-ext
7. T5-Chinese
AI recommended 7 alternatives but never named huawei-noah/Pretrained-Language-Model. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to optimize large language models for faster inference and reduced memory footprint?
you: not recommended
AI recommended (in order):
1. Hugging Face Optimum (huggingface/optimum)
2. Hugging Face Transformers (huggingface/transformers)
3. NVIDIA TensorRT
4. OpenVINO (openvinotoolkit/openvino)
5. Hugging Face Optimum (huggingface/optimum)
6. PyTorch's `torch.nn.utils.prune` (pytorch/pytorch)
7. Hugging Face Transformers (huggingface/transformers)
8. DeepSpeed (microsoft/deepspeed)
9. Hugging Face Transformers (huggingface/transformers)
10. ONNX Runtime (microsoft/onnxruntime)
11. NVIDIA TensorRT
12. OpenVINO (openvinotoolkit/openvino)
13. ONNX Runtime (microsoft/onnxruntime)
14. DeepSpeed-MII (microsoft/DeepSpeed-MII)
AI recommended 14 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 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?
If a team adopts huawei-noah/Pretrained-Language-Model in production, what risks or prerequisites should they evaluate first?
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?
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?

Embed your GEO score

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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