例文を組み込んだAlfred Workflowを作りました: Alfred Git Commit Message Example
以下転載:
| ; /usr/local/bin/nasm -f macho 32.asm && ld -macosx_version_min 10.7.0 -o 32 32.o && ./32 | |
| global start | |
| section .text | |
| start: | |
| push dword msg.len | |
| push dword msg | |
| push dword 1 | |
| mov eax, 4 |
以下転載:
| package main | |
| import ( | |
| "context" | |
| "fmt" | |
| ) | |
| type GitHub interface { | |
| CreateRelease(ctx context.Context, opt *Option) (string, error) | |
| GetRelease(ctx context.Context, tag string) (string, error) |
| # wavfile.py (Enhanced) | |
| # Date: 20190213_2328 Joseph Ernest | |
| # | |
| # URL: https://gist.github.com/josephernest/3f22c5ed5dabf1815f16efa8fa53d476 | |
| # Source: scipy/io/wavfile.py | |
| # | |
| # Added: | |
| # * read: also returns bitrate, cue markers + cue marker labels (sorted), loops, pitch | |
| # See https://web.archive.org/web/20141226210234/http://www.sonicspot.com/guide/wavefiles.html#labl | |
| # * read: 24 bit & 32 bit IEEE files support (inspired from wavio_weckesser.py from Warren Weckesser) |
コンテキスト: https://togetter.com/li/1331865
グーグルジャパンではなくてUSの本社での採用の話。私が受けたのはSoftware EngineerではなくてDeveloper Advocate。Engineering組織の下についているのでコーディング面接有り。ただし評価項目がSWEとは異なる。
| #![warn(rust_2018_idioms)] | |
| #[derive(Debug)] | |
| pub struct StrSplit<'haystack, D> { | |
| remainder: Option<&'haystack str>, | |
| delimiter: D, | |
| } | |
| impl<'haystack, D> StrSplit<'haystack, D> { | |
| pub fn new(haystack: &'haystack str, delimiter: D) -> Self { |
| use std::collections::VecDeque; | |
| use std::sync::{Arc, Condvar, Mutex}; | |
| // Flavors: | |
| // - Synchronous channels: Channel where send() can block. Limited capacity. | |
| // - Mutex + Condvar + VecDeque | |
| // - Atomic VecDeque (atomic queue) + thread::park + thread::Thread::notify | |
| // - Asynchronous channels: Channel where send() cannot block. Unbounded. | |
| // - Mutex + Condvar + VecDeque | |
| // - Mutex + Condvar + LinkedList |
This aims to be factual information about the size of large language models. None of this document was written by AI. I do not include any information from leaks or rumors. The focus of this document is on base models (the raw text continuation engines, not 'helpful chatbot/assistants'). This is a view from a few years ago to today of one very tiny fraction of the larger LLM story that's happening.