bert

> Has Google/Alphabet publicly released any of their AI models yet? You mean NLP field changing models from Google like BERT [1]? or Transformers paper [2]? or T5 model [3] (used by company doing ChatGPT like search currently on the front page on HN)? 1. https://arxiv.org/abs/1810.04805 code+models: https://github.com/google-research/bert 2. https://arxiv.org/abs/2112.04426 3. https://arxiv.org/abs/1910.10683 code+models: https://github.com/google-research/text-to-text-transfer-tra...

> resulting in large programs with lots of boilerplate That was what I was trying to say when I said "the code required to implement the challenges is large enough that they are considered too inconvenient to use". This makes sense to me. Thank you for this benchmark! I'll probably switch to spyql now from jq. > So, orjson is part of the reason why a python-based tool outperforms tools written in C, Go, etc and deserves credit. Yes, I definitely think this is worth mentioning upfront in the future, since, IIUC, orison's core uses Rust (the serde library, specifically). The initial title gave me the impression that a pure-Python json parsing-and-querying solution was the fastest out there. A parallel I think is helpful to think about is saying something like "the fastest BERT implementation is written Python[0]". While the linked implement