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TokenRhythm 发布 NeoHorse-1-4B 语言模型以实现递归自我改进

TokenRhythm 发布了 NeoHorse-1-4B,一个拥有 40 亿参数的因果语言模型。该模型是为递归自我改进设计的初始原型,并从 Qwen3.5-4B 微调而来。NeoHorse-1-4B 针对代理工具、工具使用、编码和指令遵循进行了优化,并提供了通过 Transformers、vLLM 和 SGLang 等库以及通过 Docker 进行集成的说明。 AI

影响 该模型对递归自我改进和代理工具的关注可能会影响未来人工智能的发展方法。

排序理由 新语言模型发布,来自非前沿实验室,包含其架构和预期用途的详细信息。 [lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Trending Models 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

TokenRhythm 发布 NeoHorse-1-4B 语言模型以实现递归自我改进

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
新语言模型发布,来自非前沿实验室,包含其架构和预期用途的详细信息。 [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, product
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
40 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. Hugging Face Trending Models TIER_1 Norsk(NO) · TokenRhythm ·

    TokenRhythm/NeoHorse-1-4B

    text-generation · 5,329 downloads · 775 likes