To make this practical, I first define a calibrated rubric over the digits 0-9 (there’s only one token for each digit), where each digit corresponds to a clear qualitative description. At the scoring step, I capture the model’s next-token logits and retain only the logits corresponding to those valid digit tokens. This avoids contamination from unrelated continuations such as explanation text, punctuation, or alternate formatting. After renormalizing over the restricted digit set, I interpret the resulting probabilities as a categorical score distribution.
tensor<dtype(shape, data)The dtype must be specified — there is no inference. The shape is an array of integers. The data is a flat array of values in row-major order, and its length must equal the product of the shape dimensions.
。业内人士推荐新收录的资料作为进阶阅读
#[wasm_bindgen(js_class = Foo)]
当用户对 AI 说"帮我找一款适合敏感肌的面霜"时，AI 在后台检索、筛选、比较的那个过程，就是这个隐形货架。你的产品能不能被"摆上去"，取决于一件事：AI 能不能读懂你的产品数据。传统包装是给人看的，产品数据是给 AI 看的—在隐形货架上，数据就是你的新包装。