evo-design/evo

• hightopics#1

  Add specific topics to improve categorization

  原因：

  复制粘贴的修复

  复制

  biological-foundation-model, dna-sequencing, genomics, machine-learning, deep-learning, long-context-ai, sequence-modeling, synthetic-biology, computational-biology

  待办完成忽略
• highreadme#2

  Reposition README's opening to prioritize this repo's identity

  原因：

  当前

  **We have developed a new model called Evo 2 that extends the Evo 1 model and its ideas to all domains of life. Please see https://github.com/arcinstitute/evo2 for more details.**
  
  Evo is a biological foundation model capable of long-context modeling and design.
  Evo uses the StripedHyena architecture to enable modeling of sequences at a single-nucleotide, byte-level resolution with near-linear scaling of compute and memory relative to context length.
  Evo has 7 billion parameters and is trained on OpenGenome, a prokaryotic whole-genome dataset containing ~300 billion tokens.

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  Evo is a biological foundation model capable of long-context modeling and design, specifically for DNA sequence analysis from molecular to genome scale. It uses the StripedHyena architecture for single-nucleotide, byte-level resolution. Evo has 7 billion parameters and is trained on OpenGenome, a prokaryotic whole-genome dataset containing ~300 billion tokens.
  
  We have also developed Evo 2, which extends the Evo 1 model and its ideas to all domains of life; please see https://github.com/arcinstitute/evo2 for more details.

  待办完成忽略
• mediumhomepage#3

  Add a homepage URL to the repository metadata

  原因：

  复制粘贴的修复

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  https://arcinstitute.org/

  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

  What AI models are available for long-context biological sequence analysis and design?

  你：未被推荐
  AI 推荐顺序：

  1. ESM-2
  2. AlphaFold2
  3. AlphaFold3
  4. ProGen
  5. OpenFold
  6. Tranception
  7. ProtGPT2
  8. DNABERT
  9. RNABERT

  AI 推荐了 9 个替代方案，却始终没点名 evo-design/evo。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  How can I generate synthetic DNA sequences using a large-scale genomic language model?

  你：未被推荐
  AI 推荐顺序：

  1. HyenaDNA
  2. GenSLMs
  3. Nucleotide Transformer
  4. DNABERT
  5. Genomic Foundation Models
  6. PyTorch
  7. TensorFlow
  8. GPT-2/GPT-3
  9. Hugging Face Transformers

  AI 推荐了 9 个替代方案，却始终没点名 evo-design/evo。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of evo-design/evo?

  pass
  ✓AI 明确点名了 evo-design/evo

  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 evo-design/evo in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 evo-design/evo

  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 evo-design/evo solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 evo-design/evo

  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？