RRepoGEO

REPOGEO REPORT · LITE

dandelionsllm/pandallm

Default branch main · commit 4a47ecd4 · scanned 5/16/2026, 12:37:31 AM

GitHub: 1,034 stars · 76 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 dandelionsllm/pandallm, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    chinese-llm, large-language-models, llm-finetuning, llm-deployment, llama, llmops, nlp, open-source-llm
  • highabout#2
    Add a concise English description to the 'About' section

    Why:

    CURRENT
    Panda项目是于2023年5月启动的开源海外中文大语言模型项目,致力于大模型时代探索整个技术栈,旨在推动中文自然语言处理领域的创新和合作。
    COPY-PASTE FIX
    PandaLLM is an open-source project dedicated to developing, fine-tuning, and deploying Chinese large language models (LLMs) based on LLaMA, along with a comprehensive LLMOps toolkit for training, inference, and deployment.
  • mediumhomepage#3
    Add the official project homepage URL

    Why:

    COPY-PASTE FIX
    http://pandallm.ai/

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 dandelionsllm/pandallm
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 1×
  2. PaddlePaddle/Paddle · recommended 1×
  3. mindspore-ai/mindspore · recommended 1×
  4. open-mmlab/OpenMMLab · recommended 1×
  5. microsoft/DeepSpeed · recommended 1×
  • CATEGORY QUERY
    What are effective open-source platforms for developing and deploying Chinese large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. PaddlePaddle (PaddlePaddle/Paddle)
    3. MindSpore (mindspore-ai/mindspore)
    4. OpenMMLab (open-mmlab/OpenMMLab)
    5. DeepSpeed (microsoft/DeepSpeed)
    6. ColossalAI (hpcaitech/ColossalAI)

    AI recommended 6 alternatives but never named dandelionsllm/pandallm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking robust tools to efficiently fine-tune and deploy LLaMA-based models for production environments.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PEFT
    3. TRL
    4. optimum
    5. AWS SageMaker
    6. Google Cloud Vertex AI
    7. Hugging Face Inference Endpoints
    8. vLLM
    9. Ray
    10. Ray Train
    11. Ray Serve
    12. PyTorch FSDP
    13. DeepSpeed
    14. NVIDIA Triton Inference Server
    15. OpenVINO
    16. ONNX Runtime

    AI recommended 16 alternatives but never named dandelionsllm/pandallm. 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 dandelionsllm/pandallm?
    pass
    AI did not name dandelionsllm/pandallm — 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 dandelionsllm/pandallm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dandelionsllm/pandallm 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 dandelionsllm/pandallm solve, and who is the primary audience?
    pass
    AI named dandelionsllm/pandallm explicitly

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

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dandelionsllm/pandallm — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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