TencentARC/LLaMA-Pro

• highreadme#1

  Reposition the README's opening to clearly state LLaMA-Pro's nature as a model/methodology

  Why:

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  # LLaMA Pro: Progressive LLaMA with Block Expansion
  <p align="center">
  📃 <a href="https://arxiv.org/abs/2401.02415" target="_blank">Paper</a> • 🤗 <a href="https://huggingface.co/TencentARC/LLaMA-Pro-8B" target="_blank">Demo & Model</a> 
  </p>
  
  LLaMA-Pro introduces a novel progressive pre-training strategy with block expansion, significantly enhancing the mathematical reasoning, coding abilities, and context window of large language models like LLaMA and Mistral.

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• hightopics#2

  Add more specific topics to reflect the project's methodology and application areas

  Why:

  CURRENT

  llama, llama2, llm

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  llama, llama2, llm, large-language-models, llm-training, model-expansion, mathematical-reasoning, code-generation, progressive-training, acl-2024

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• mediumreadme#3

  Emphasize the core differentiator and methodology early in the README

  Why:

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  Our approach efficiently extends the context window and improves performance by selectively adding and training new expert blocks on longer sequences, a form of Mixture-of-Experts. This method has yielded superior results on benchmarks for math and code.

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Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  How can I improve the mathematical reasoning and coding abilities of open-source language models?

  you: not recommended
  AI recommended (in order):

  1. MATH Dataset
  2. GSM8K
  3. CodeContests
  4. APPS
  5. DeepMind's AlphaCode Dataset
  6. Lean
  7. Coq
  8. Stack Overflow
  9. GitHub Code Snippets
  10. PPO (Proximal Policy Optimization)
  11. DPO (Direct Preference Optimization)
  12. Constitutional AI (Anthropic)
  13. Self-Refine (Google DeepMind)
  14. Chain-of-Thought (CoT) Prompting
  15. Program-Aided Language Models (PAL)
  16. LongFormer
  17. Perceiver IO
  18. Hyena Hierarchy
  19. Reformer
  20. BigBird
  21. ToolFormer (Meta AI)
  22. Wolfram Alpha
  23. SymPy
  24. MRKL (Modular Reasoning, Knowledge and Language)

  AI recommended 24 alternatives but never named TencentARC/LLaMA-Pro. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  What techniques are available for progressively expanding and enhancing pre-trained large language models?

  you: not recommended
  AI recommended (in order):

  1. RoBERTa
  2. BioBERT
  3. SciBERT
  4. BloombergGPT
  5. Hugging Face Transformers Library
  6. PEFT
  7. LoRA
  8. QLoRA
  9. Prefix-Tuning
  10. OpenAI API Fine-tuning
  11. FAISS
  12. Pinecone
  13. LangChain
  14. LlamaIndex
  15. Mixtral 8x7B
  16. GPT-4
  17. OpenAI Function Calling
  18. Google Gemini's Tool Use

  AI recommended 18 alternatives but never named TencentARC/LLaMA-Pro. This is the gap to close.

  Show full AI answer

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of TencentARC/LLaMA-Pro?

  pass
  ✓AI named TencentARC/LLaMA-Pro explicitly

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

• If a team adopts TencentARC/LLaMA-Pro in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI named TencentARC/LLaMA-Pro 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 TencentARC/LLaMA-Pro solve, and who is the primary audience?

  pass
  ✓AI named TencentARC/LLaMA-Pro explicitly

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