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English(EN) unsloft's Qwen3.8-27B-GGUF is pulling 5.1M downloads in 30 days—more than most open-weight models see in a year. That Apache-2.0 license matters when you’re dep

量化后的 Qwen3.8-27B-GGUF 模型在 30 天内下载量达 580 万次

unsloth/Qwen3.8-27B-GGUF 模型在发布后的 30 天内,在 Hugging Face 上获得了显著的采用,下载量达到 580 万次。该量化模型的快速普及凸显了其 Apache-2.0 许可证对于大规模部署的重要性。olud.ai 正在密切关注该模型的性能,将其作为开源 AI 趋势的指标。 AI

影响 凸显了量化、允许性许可的开源模型在广泛部署方面的强劲采用。

排序理由 该集群报告了有关开源 AI 模型的下载数量和许可信息,属于工具类别,而非前沿发布。

在 Mastodon — fosstodon.org 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

量化后的 Qwen3.8-27B-GGUF 模型在 30 天内下载量达 580 万次

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该集群报告了有关开源 AI 模型的下载数量和许可信息,属于工具类别,而非前沿发布。
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报道来源 [2]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    unsloth/Qwen3.8-27B-GGUF:30天在HF上下载量达580万。这是一个驱动大规模采用的量化模型——正是olud.ai每小时跟踪的那种信号。

    unsloth/Qwen3.8-27B-GGUF: 5.8M downloads in 30 days on HF. That’s a quantized model driving serious adoption – exactly the kind of signal olud.ai tracks hourly. https:// olud.ai/#leaderboard # OpenSource # AI # HuggingFace

  2. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    unsloft 的 Qwen3.8-27B-GGUF 在 30 天内下载量达到 510 万次——超过了大多数开源模型一年的下载量。Apache-2.0 许可证在您进行 dep 时很重要

    unsloft's Qwen3.8-27B-GGUF is pulling 5.1M downloads in 30 days—more than most open-weight models see in a year. That Apache-2.0 license matters when you’re deploying at scale. https:// olud.ai/#leaderboard # OpenSource # AI # HuggingFace