SafeAILab/EAGLE

• highreadme#1

  Reposition README opening to highlight category and competitive edge

  原因：

  当前

  EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency) is a new baseline for fast decoding of Large Language Models (LLMs) with provable performance maintenance. This approach involves extrapolating the second-top-layer contextual feature vectors of LLMs, enabling a significant boost in generation efficiency.

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  复制

  EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency) is the **fastest speculative decoding method** for Large Language Models (LLMs) with provable performance maintenance. By extrapolating second-top-layer contextual feature vectors, EAGLE significantly boosts generation efficiency, outperforming alternatives like Medusa and Lookahead.

  待办完成忽略
• mediumtopics#2

  Expand repository topics for broader LLM acceleration queries

  原因：

  当前

  large-language-models, llm-inference, speculative-decoding

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  large-language-models, llm-inference, speculative-decoding, llm-acceleration, inference-optimization, deep-learning-inference, ai-performance, model-acceleration

  待办完成忽略
• mediumreadme#3

  Clarify the project's license in the README

  原因：

  复制粘贴的修复

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  ## License
  This project is primarily licensed under the Apache 2.0 License. Please refer to the `LICENSE` file for full details, as it may include additional terms.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How can I accelerate large language model inference without sacrificing accuracy?

  你：未被推荐
  AI 推荐顺序：

  1. NVIDIA TensorRT
  2. OpenVINO
  3. ONNX Runtime
  4. DeepSpeed
  5. Hugging Face Optimum
  6. PyTorch Compile (TorchDynamo)
  7. FasterTransformer

  AI 推荐了 7 个替代方案，却始终没点名 SafeAILab/EAGLE。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What are the most efficient methods for speculative decoding to speed up LLM generation?

  你：未被推荐
  AI 推荐顺序：

  1. Medusa
  2. SpecInfer
  3. DeepSpeed-FastGen
  4. Google's Lookahead Decoding
  5. Self-Speculative Decoding
  6. Block-Recurrent Transformers

  AI 推荐了 6 个替代方案，却始终没点名 SafeAILab/EAGLE。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of SafeAILab/EAGLE?

  pass
  ✓AI 明确点名了 SafeAILab/EAGLE

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts SafeAILab/EAGLE in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 SafeAILab/EAGLE

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo SafeAILab/EAGLE solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 SafeAILab/EAGLE

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？