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Efficient Linuxコマンドライン
Linuxスキルをレベルアップする実用的な実践書。本書では、コマンドを組み合わせて複雑なコマンドを作成することで、手動で行われているタスクを自動化するための方法を学びます。具体的には、パスワードの管理、大量のテストファイルの生成、テキストファイルを変換してデータベースのように扱う方法など、現実的なビジネスの問題を解決する方法を明らかにします。単なるテクニックではなく、背後で何が行われているかについても学べるので、Linuxのシェルに対する理解が深まります。それと同時に、Linuxコマンドに関するさらに上級レベルの知識とテクニックが身につきます。 賞賛の声 監訳者まえがき まえがき 第I部 主要な概念 1章 コマンドの組み合わせ 1.1 入力、出力、パイプ 1.2 コマンドラインに取り掛かるための6個のコマンド 1.2.1 コマンド① wc 1.2.2 コマンド② head 1.2.3 コマ
GitHub - google/wireit: Wireit upgrades your npm/pnpm/yarn scripts to make them smarter and more efficient.
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GitHub - pkolaczk/fclones: Efficient Duplicate File Finder
Efficient duplicate file finder and remover This is the repo for command line fclones and its core libraries. For the desktop frontend, see fclones-gui. fclones is a command line utility that identifies groups of identical files and gets rid of the file copies you no longer need. It comes with plenty of configuration options for controlling the search scope and offers many ways of removing duplica
GitHub - smocker-dev/smocker: Smocker is a simple and efficient HTTP mock server and proxy
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cvpaper.challenge の メタサーベイ発表スライドです。 cvpaper.challengeはコンピュータビジョン分野の今を映し、トレンドを創り出す挑戦です。論文サマリ作成・アイディア考案・議論・実装・論文投稿に取り組み、凡ゆる知識を共有します。 http://xpaperchallenge.org/cv/ Read less
OCaml Programming: Correct + Efficient + Beautiful — OCaml Programming: Correct + Efficient + Beautiful
Preface About This Book Installing OCaml Introduction 1. Better Programming Through OCaml 1.1. The Past of OCaml 1.2. The Present of OCaml 1.3. Look to Your Future 1.4. A Brief History of CS 3110 1.5. Summary 2. The Basics of OCaml 2.1. The OCaml Toplevel 2.2. Compiling OCaml Programs 2.3. Expressions 2.4. Functions 2.5. Documentation 2.6. Printing 2.7. Debugging 2.8. Summary 2.9. Exercises OCaml
Cerebras-GPT: A Family of Open, Compute-efficient, Large Language Models - Cerebras
Cerebras-GPT: A Family of Open, Compute-efficient, Large Language Models Cerebras open sources seven GPT-3 models from 111 million to 13 billion parameters. Trained using the Chinchilla formula, these models set new benchmarks for accuracy and compute efficiency. Abstract State-of-the-art language models are extremely challenging to train; they require huge compute budgets, complex distributed com
GitHub - asg017/sqlite-vss: A SQLite extension for efficient vector search, based on Faiss!
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GitHub - awslabs/llrt: LLRT (Low Latency Runtime) is an experimental, lightweight JavaScript runtime designed to address the growing demand for fast and efficient Serverless applications.
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GitHub - Sysinternals/ProcMon-for-Linux: Procmon is a Linux reimagining of the classic Procmon tool from the Sysinternals suite of tools for Windows. Procmon provides a convenient and efficient way for Linux developers to trace the syscall activity on the
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TL;DR: DuckDB-Wasm is an in-process analytical SQL database for the browser. It is powered by WebAssembly, speaks Arrow fluently, reads Parquet, CSV and JSON files backed by Filesystem APIs or HTTP requests and has been tested with Chrome, Firefox, Safari and Node.js. You can try it in your browser at shell.duckdb.org or on Observable. DuckDB-Wasm is fast! If you're here for performance numbers, h
GitHub - google/forma: An efficient vector-graphics renderer
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Transformer model architectures have garnered immense interest lately due to their effectiveness across a range of domains like language, vision and reinforcement learning. In the field of natural language processing for example, Transformers have become an indispensable staple in the modern deep learning stack. Recently, a dizzying number of "X-former" models have been proposed - Reformer, Linfor
GitHub - piscinajs/piscina: A fast, efficient Node.js Worker Thread Pool implementation
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GitHub - hora-search/hora: 🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
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Shota Imai@えるエル on Twitter: "深層学習を使う場合の学習効率化,高速化などの手法,テクニックなどが非常に網羅的にまとめられたサーベイ論文です 研究や開発で深層学習を使う人には非常に重要な知見の宝庫 "Efficient Deep Learning: A Surv… https://t.co/wxaJZOzttb"
深層学習を使う場合の学習効率化,高速化などの手法,テクニックなどが非常に網羅的にまとめられたサーベイ論文です 研究や開発で深層学習を使う人には非常に重要な知見の宝庫 "Efficient Deep Learning: A Surv… https://t.co/wxaJZOzttb
Arm64 on GitHub Actions: Powering faster, more efficient build systems
AI & MLLearn about artificial intelligence and machine learning across the GitHub ecosystem and the wider industry. Generative AILearn how to build with generative AI. GitHub CopilotChange how you work with GitHub Copilot. LLMsEverything developers need to know about LLMs. Machine learningMachine learning tips, tricks, and best practices. How AI code generation worksExplore the capabilities and be
GitHub - raghavan/PdfGptIndexer: An efficient tool for indexing and searching PDF text data using OpenAI API and FAISS (Facebook AI Similarity Search) index, designed for rapid information retrieval and superior search accuracy.
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GitHub - frehner/modern-guide-to-packaging-js-library: A guide to help ensure your JavaScript library is the most compatible, fast, and efficient library you can make.
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This year, the YJIT team and I have gotten a paper accepted at MPLR 2023 (Managed Programming Languages and Runtimes), which is now freely available through ACM open access. The paper, titled “Evaluating YJIT’s Performance in a Production Context: A Pragmatic Approach”, goes into details of the strategy taken to evaluate YJIT’s performance in a production context. One of our key findings, when com
GitHub - pascalw/kindle-dash: Power efficient dashboard for Kindle 4 NT devices
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GitHub - ezrosent/frawk: an efficient awk-like language
Note (2024, ezrosent@) While the policy on bugs and feature requests remains unchanged I've had much less time over the last 1-2 years to devote to bug fixes and feature requests for frawk. Other awks are more actively maintained, and CSV support is now a much more common feature in awk compared to when this project started; I'll update this notice if frawk's status changes. frawk is a small progr
効率的node_modules 内のファイルは単一のコンテンツアドレス指定可能なストレージから複製またはハードリンクされます。
SIEVE: an Efficient Turn-Key Eviction Algorithm for Web Caches - SIEVE is simpler than LRU
SIEVE is simpler than LRU¶ Caching is a method of storing temporary data for quick access to keep the online world running smoothly. But with limited space comes a critical decision: what to keep and discard. This is where eviction algorithms come into play. Our team recently designed a new cache eviction algorithm called SIEVE: it is very effective and simple with just one queue. Website Paper Up
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The complexity of writing an efficient NodeJS Docker image - Specfy
Docker is an invaluable tool for managing containers, but it can be challenging to grasp its inner workings, especially for newcomers. While modern hosting platforms like Vercel and Netlify often eliminate the need for writing Dockerfiles for NodeJS processes, understanding Docker optimization becomes crucial when handling your infrastructure. By achieving optimal efficiency, you can save both tim
論文読みメモ： Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting - クッキーの日記
2021-02-14 3枚目の絵を修正しました。以下の論文を読みます。私の誤りは私に帰属します。お気付きの点がありましたらご指摘いただけますと幸いです。Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, Wancai Zhang. Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting. arXiv preprint arXiv:2012.07436, 2020. [2012.07436] Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting GitHub - zhouhaoyi
GitHub - microsoft/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
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GitHub - pytorch-labs/gpt-fast: Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.
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GitHub - hpcaitech/Open-Sora: Open-Sora: Democratizing Efficient Video Production for All
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GitHub - huggingface/peft: 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
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LLaMA: Open and Efficient Foundation Language Models - Meta Research | Meta Research
We introduce LLaMA, a collection of foundation language models ranging from 7B to 65B parameters. We train our models on trillions of tokens, and show that it is possible to train state-of-the-art models using publicly available datasets exclusively, without resorting to proprietary and inaccessible datasets. In particular, LLaMA-13B outperforms GPT-3 (175B) on most benchmarks, and LLaMA-65B is co
Magika: AI powered fast and efficient file type identification
The latest news from Google on open source releases, major projects, events, and student outreach programs. Today we are open-sourcing Magika, Google’s AI-powered file-type identification system, to help others accurately detect binary and textual file types. Under the hood, Magika employs a custom, highly optimized deep-learning model, enabling precise file identification within milliseconds, eve
We present QLoRA, an efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance. QLoRA backpropagates gradients through a frozen, 4-bit quantized pretrained language model into Low Rank Adapters~(LoRA). Our best model family, which we name Guanaco, outperforms all previous openly rel
Want help enforcing rules? 👮 Gently nudge you and your team into ECSS. Install the Stylelint config Eager to build something? 🏁 A quick & efficient starting point is within reach! Clone the scaffolding library (WIP) Want to know the beast? 📰 Go ahead and see what you think of it! Dive into ECSS rules Curious about it all? Well, keep scrolling! Why ECSS? Because CSS as a language is misunderstoo
Patterns for Memory Efficient DOM Manipulation with Modern Vanilla JavaScript – Frontend Masters Boost
Patterns for Memory Efficient DOM Manipulation with Modern Vanilla JavaScript July 29, 2024 I’ll discuss best practices to avoid excess memory usage when managing updating the DOM to make your apps blazingly fast™️. DOM: Document Object Model – A Brief OverviewWhen you render HTML, the live view of those rendered elements in the browser is called the DOM. This is what you’ll see in your developer
GitHub - RUC-NLPIR/FlashRAG: ⚡FlashRAG: A Python Toolkit for Efficient RAG Research
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【マイクラ1.21～1.16】簡単&超高効率なゾンビピグリントラップ 作り方解説！もう金と腐肉には困らない！Minecraft Easy & High Efficient Gold Farm【マインクラフト/Java Edition】 - じゃがいもゲームブログ
皆様こんばんは！ 如何お過ごしでしょうか。 今回は、簡単&超高効率なゾンビピグリントラップの作り方について解説します！ 簡単に作れて、超高効率です！1時間くらいで作れて、1時間で金ブロック128個手に入ります。では、さっそく作り方を解説したいと思います。よろしくお願いいたします。 必要素材は以下の通りです。 マグマブロック4320個、ガラス541個、足場128個、トラップドア92個、チェスト12個、ホッパー12個、カーペット10個、建築ブロック6個、カメの卵6個、あと仮ブロック64個あれば作れます。足場ははしごで代用可です。 大量のマグマブロックが必要になりますが、その他はカメの卵くらいしかレアなアイテムはありません。 今回は湧き層を6層作りますが、4層でも十分な性能になります。4層つくる場合はマグマブロック2880個あれば作れます。1層あたり720個のマグマブロックを使います。 ご自身の
GitHub - anfragment/zen: Simple, free and efficient ad-blocker and privacy guard for Windows, macOS and Linux
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効率的学習 / Efficient Training（メタサーベイ）
DuckDB-Wasm: Efficient Analytical SQL in the Browser
Efficient Transformers: A Survey
GPT-4o mini: advancing cost-efficient intelligence
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