Nathan Lambert· @natolambert · X·· 3 小时前AI 评分29
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我们方法论中一个已被修复的缺口——之前没有纳入本地模型（GGUF、AWQ、ONNX 等）——曾导致数据呈现下滑。早前这些模型远更难追踪，更接近舍入误差。如今它们正在激增。我们已更新管线来追踪这些模型！
正文
A gap that has been fixed in our methodology that highlighted a decline was not including local models (GGUF, AWQ, ONNX, etc). Earlier, these were far harder to track and closer to a rounding error. Now, they're surging. We updated our pipeline to track these models!
We've been monitoring a decline in HuggingFace downloads across the top open LLMs we track for interconnects. It looks like there was a slight change in counting of downloads, as we saw a ~30% download rate drop for many top models, but this is continuing over time. What else do people think it may be?在 X 查看被引用的帖子
来源：Nathan Lambert · x.com