about everything, and I rather people read documentation about it instead of
Sounds promising, right? I spent some time testing it, but results were poor—high false positives and false negatives, no clear threshold for reliable classification. Plus, it suffers from high inference costs, poor cross-model generalization, difficulty deploying large models locally, and lack of access to closed-source model weights. All in all, it’s neither elegant nor reliable.
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When shown a diagram of a vulva, 24 percent thought it was a heart, 13 percent thought it was a vagina (which is the internal organ, not external as the vulva is), and 10 percent believed it to be ovaries.
。关于这个话题，Safew下载提供了深入分析
Фото: Phil Noble / Reuters
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