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English(EN) I'm not real sure what is going on the back-end - but it seems like AI Flow wants to load 32K of tokens up with each request - and the machine I'm using doesn't

AI Flow 在本地设置中遇到困难，用户报告性能缓慢

作者 PulseAugur 编辑部 · [2 个来源] ·

一位用户在尝试在本地运行 AI Flow 时遇到性能问题，特别是处理大量 token 时。用户指出，他们的旧机器难以满足 AI Flow 的需求，在使用 LM Studio 作为后端时导致结果缓慢或无法运行。虽然 LM Studio 提供了一些功能，但设置比预期的要慢得多，一个简单的测试需要很长时间才能完成。 AI

影响 本地 AI 开发工具可能需要大量的硬件资源和优化才能高效运行。

排序理由 用户报告了特定软件工具的问题，而非前沿发布或重大行业事件。

在 Mastodon — mastodon.social 阅读 →

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

AI Flow 在本地设置中遇到困难，用户报告性能缓慢

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Tool
用户报告了特定软件工具的问题，而非前沿发布或重大行业事件。
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报道来源 [2]

  1. Mastodon — mastodon.social TIER_1 English(EN) · kd8bxp ·

    我不确定后端发生了什么——但似乎AI Flow每次请求都想加载32K个令牌——而我正在使用的机器没有

    I'm not real sure what is going on the back-end - but it seems like AI Flow wants to load 32K of tokens up with each request - and the machine I'm using doesn't like that (maybe) - of course it's an older machine, it really shouldn't be able to run any model - but if I just use L…

  2. Mastodon — mastodon.social TIER_1 English(EN) · kd8bxp ·

    我正在尝试使用 M5Stack 的 AI Flow 在本地运行，后端使用 LM Studio - 最初我想使用的机器没有正确的指令集

    I'm attempting to use AI Flow from M5Stack locally with LM Studio on the back end - the original machine I wanted to use didn't have the right instruction set and refused to load any models - so I move to a more up to date machine - I knew it was never going to break any speed re…

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