一位r/MachineLearning子版块的用户正在寻求有关在移动硬件上部署BiRefNet模型的帮助，特别是高通的NPUs和GPUs。由于BiRefNet的可变形卷积的复杂性，用户遇到了困难，并希望为项目实现亚秒级延迟。他们请求有此特定部署挑战经验的人提供帮助。 AI
排序理由 这是一个论坛上的用户生成问题，而不是关于新技术发布的正式公告或发布。
AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →
用户寻求在移动硬件上部署BiRefNet的帮助
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- Signal score
- 0 / 100
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- Newsworthiness bucket
- Meme
- 这是一个论坛上的用户生成问题，而不是关于新技术发布的正式公告或发布。
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- 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
- infra
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- Breaking (< 6h)
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完整方法见我们的编辑标准。
报道来源 [1]
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有人在移动NPU和GPU上成功运行BiRefNet吗？特别是高通[D]
<!-- SC_OFF --><div class="md"><p>I've been trying to get BiRefNet to work on Qualcomm's mobile GPUs and NPUs. But i guess it's deformable convolutions are pretty complex for those chips. I want a sub second latency performance on these chips for a project I'm doing</p> <p>Has an…