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marin-community/levanter

默认分支 main · commit 982cef7f · 扫描时间 2026/6/12 02:38:22

星标 709 · Fork 120

AI 可见性总分
35 /100
亟需修复
品类召回
0 / 2
在所有问题中均未被推荐
规则结果
通过 1 · 警告 1 · 失败 0
客观元数据检查
AI 认识你的名字
3 / 3
直接询问时,AI 是否点名你的仓库
如何阅读这份报告

行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 marin-community/levanter 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。

行动计划 — 可复制粘贴的修复

3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。

整体方向
  • hightopics#1
    Add relevant topics to the repository

    原因:

    复制粘贴的修复
    jax, llm, large-language-models, deep-learning, machine-learning, foundation-models, named-tensors, haliax, distributed-training
  • highreadme#2
    Reframe README's opening to clarify Levanter's current utility despite merger

    原因:

    当前
    # Levanter
    
    > [!IMPORTANT]
    > **Levanter has been merged into Marin** as of November 2025.
    >
    > All active development now happens in the Marin monorepo at `lib/levanter/`.
    >
    > Issues**: Please open new issues at marin-community/marin
    > Pull Requests**: Submit new PRs to marin-community/marin
    > Installation**: `pip install levanter` still works
    >
    > See marin#1773 and marin#1723 for details on the merger.
    
    <a href="https://github.com/stanford-crfm/levanter/actions?query=branch%3Amain++">
        
    </a>
    <a href="https://levanter.readthedocs.io/en/latest/?badge=latest">
        
    </a>
    <a href="">
    
    </a>
    <a href="https://https://pypi.org/project/levanter/">
        
    </a>
    
    > *You could not prevent a thunderstorm, but you could use the electricity; you could not direct the wind, but you could trim your sail so as to propel your vessel as you pleased, no matter which way the wind blew.* <br/>
    > — Cora L. V. Hatch
    
    Levanter is a framework for training large language models (LLMs) and other foundation models that strives for legibility, scalability, and reproducibility:
    复制粘贴的修复
    # Levanter: A Legible, Scalable, Reproducible Framework for JAX-based Foundation Models
    
    Levanter is a powerful framework for training large language models (LLMs) and other foundation models, designed for legibility, scalability, and reproducibility. It leverages our named tensor library Haliax to write easy-to-follow, composable deep learning code, while still being high performance and capable of scaling to large models on various hardware, including GPUs and TPUs.
    
    > [!IMPORTANT]
    > **Levanter has been merged into Marin** as of November 2025.
    >
    > All active development now happens in the Marin monorepo at `lib/levanter/`.
    >
    > Issues**: Please open new issues at marin-community/marin
    > Pull Requests**: Submit new PRs to marin-community/marin
    > Installation**: `pip install levanter` still works
    >
    > See marin#1773 and marin#1723 for details on the merger.
    
    <a href="https://github.com/stanford-crfm/levanter/actions?query=branch%3Amain++">
        
    </a>
    <a href="https://levanter.readthedocs.io/en/latest/?badge=latest">
        
    </a>
    <a href="">
    
    </a>
    <a href="https://https://pypi.org/project/levanter/">
        
    </a>
    
    > *You could not prevent a thunderstorm, but you could use the electricity; you could not direct the wind, but you could trim your sail so as to propel your vessel as you pleased, no matter which way the wind blew.* <br/>
    > — Cora L. V. Hatch
  • mediumabout#3
    Enhance the repository description with explicit keywords

    原因:

    当前
    Legible, Scalable, Reproducible Foundation Models with Named Tensors and Jax
    复制粘贴的修复
    A legible, scalable, and reproducible JAX-based framework for training Large Language Models (LLMs) and other foundation models with named tensors.

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

品类可见性 — 真正的 GEO 测试

向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?

各模型使用同一组问题 — 切换标签对比回答与排名。

召回
0 / 2
0% 的问题里出现了 marin-community/levanter
平均排名
越小越好。#1 表示首位推荐。
声量占比
0%
在所有被点名的工具中,你占了多少?
头号对手
Keras
在 2 个问题中被推荐 2 次
竞品排行
  1. Keras · 被推荐 2 次
  2. PyTorch · 被推荐 2 次
  3. JAX · 被推荐 1 次
  4. Flax · 被推荐 1 次
  5. Orbax · 被推荐 1 次
  • 品类问题
    Seeking a scalable and reproducible framework for training large language models using Jax.
    你:未被推荐
    AI 推荐顺序:
    1. JAX
    2. Flax
    3. Orbax
    4. JAX-Pallas
    5. Hugging Face Transformers
    6. Haiku
    7. Equinox
    8. Trax

    AI 推荐了 8 个替代方案,却始终没点名 marin-community/levanter。这就是要补上的差距。

    查看 AI 完整回答
  • 品类问题
    What tools offer legible deep learning code using named tensors for complex models?
    你:未被推荐
    AI 推荐顺序:
    1. TensorFlow
    2. Keras
    3. tf.experimental.NamedTensor
    4. PyTorch
    5. einops (einops/einops)
    6. JAX (google/jax)
    7. Keras
    8. PyTorch
    9. dm-tree (deepmind/tree)

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

    查看 AI 完整回答

客观检查

针对 AI 引擎最看重的元数据信号的规则审计。

  • Metadata completeness
    warn

    建议:

  • README presence
    pass

自指检查

当被直接问到你时,AI 是否还知道你的仓库存在?

  • Compared to common alternatives in this category, what is the core differentiator of marin-community/levanter?
    pass
    AI 明确点名了 marin-community/levanter

    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 marin-community/levanter in production, what risks or prerequisites should they evaluate first?
    pass
    AI 明确点名了 marin-community/levanter

    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 marin-community/levanter solve, and who is the primary audience?
    pass
    AI 明确点名了 marin-community/levanter

    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?

嵌入你的 GEO 徽章

把这个徽章贴进 marin-community/levanter 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。

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订阅 Pro,解锁深度诊断

marin-community/levanter — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。

  • 深度报告每月 10 次
  • 无品牌品类查询5,轻量 2
  • 优先行动项8,轻量 3