並び順

ブックマーク数

期間指定

  • から
  • まで

1 - 25 件 / 25件

新着順 人気順

python dictionary items methodの検索結果1 - 25 件 / 25件

  • 【C#】何故 C# を好むのか。~他の言語と比較しながら~ - ねののお庭。

    世の中には多くの C# に関する誤解が蔓延っています。 偏見にも満ちています。 そして技術的に正しい批判ではなく、根本的に技術的に誤った批判ばかりで正直悲しい。 技術的に正しい形の批判なら「お、そうだな。そしてそれの解決策はですねぇ...(ニヤニヤ)」となるのですが...。 そして C# 界隈から一歩出ると、「え、C# で作ってるの!?なんで??」とか言われる事が非常に多い始末。 C# 大好きマンとしては非常に嘆かわしい。 嘆かわしい限りなので、ここでなぜ C# を私が好むか、そして何故ソフトウェアの開発に向いているかを語りたいと思います。そして誤解が解けたら嬉しい。ついでに C# を書きたいと思ってくれたら嬉しい。 想定読者 前書きという名の予防線 事前知識: C# と .NET C# はパフォーマンスの高い言語 C# はビルドも高速 C# はオープンソースかつクロスプラットフォーム 言

      【C#】何故 C# を好むのか。~他の言語と比較しながら~ - ねののお庭。
    • 敵対的プロンプト技術まとめ - Qiita

      こんにちは@fuyu_quantです。 この記事はLLM Advent Calender 2023 17日目の記事です。 よかったらプライベートで作成したData Science wikiのGPTsも見て下さい! はじめに 今回は敵対的なプロンプト技術についてまとめました.まとめ方は主に,Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition というLLMに対する敵対的なプロンプト技術に関してまとめた論文を参考にしています.本記事の内容が世の中のLLMを使ったサービスの機能向上の役に立てれば幸いです. ※世の中のLLMサービスが敵対的なプロンプト手法に対応できるように公開をしたものであり,利用を

        敵対的プロンプト技術まとめ - Qiita
      • The Prompt Engineering Playbook for Programmers

        Developers are increasingly relying on AI coding assistants to accelerate our daily workflows. These tools can autocomplete functions, suggest bug fixes, and even generate entire modules or MVPs. Yet, as many of us have learned, the quality of the AI’s output depends largely on the quality of the prompt you provide. In other words, prompt engineering has become an essential skill. A poorly phrased

          The Prompt Engineering Playbook for Programmers
        • GitHub - modelcontextprotocol/servers: Model Context Protocol Servers

          Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. 2slides - An MCP server that provides tools to convert content into slides/PPT/presentation or generate slides/PPT/presentation with user intention. ActionKit by Paragon - Connect to 130+ SaaS inte

            GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
          • GPT in 60 Lines of NumPy | Jay Mody

            January 30, 2023 In this post, we'll implement a GPT from scratch in just 60 lines of numpy. We'll then load the trained GPT-2 model weights released by OpenAI into our implementation and generate some text. Note: This post assumes familiarity with Python, NumPy, and some basic experience with neural networks. This implementation is for educational purposes, so it's missing lots of features/improv

            • Writing a C compiler in 500 lines of Python

              A few months ago, I set myself the challenge of writing a C compiler in 500 lines of Python1, after writing my SDF donut post. How hard could it be? The answer was, pretty hard, even when dropping quite a few features. But it was also pretty interesting, and the result is surprisingly functional and not too hard to understand! There's too much code for me to comprehensively cover in a single blog

              • How to create a Python package in 2022

                Photo by Claudio Schwarz on Unsplash. How to create a Python package? In order to create a Python package, you need to write the code that implements the functionality you want to put in your package, and then you need to publish it to PyPI. That is the bare minimum. Nowadays, you can also set up a variety of other things to make your life easier down the road: continuous testing of your package;

                  How to create a Python package in 2022
                • What's new in Python 3.11?

                  What's new in Python 3.11?Built-in TOML support, better exceptions, and typing improvements. By Tushar·InsightsPython The first beta release of Python 3.11 is out, bringing some fascinating features for us to tinker with. This is what you can expect to see in 2022's release of Python later this year. Even better error messagesPython 3.10 gave us better error messages in various regards, but Python

                    What's new in Python 3.11?
                  • ​Getting Started with Python

                    Python is a powerful programming language that provides many packages that we can use. Using the versatile Python programming language, we can develop the following: AutomationDesktop applicationAndroidWebIoT home automationData Science and the list goes on.In this article, our primary focus will be knowing how to start learning Python and the essentials required to be a data scientist. Below is t

                      ​Getting Started with Python
                    • ChatGPT x LangChain で独自ドキュメントのベクターストア検索をチューニングする - GMOインターネットグループ グループ研究開発本部

                      D.Mです。 ChatGPT を開発の現場で活かしていくためにベクターストア活用の方法を検証しました。 結論ファースト A. ベクターストアに入れる元ネタドキュメントの抽出 ⇒ unstructured が使えるかも B. ベクターストアに入れる元ネタドキュメントのチャンク分け ⇒ タイトル。キーワードをメタデータで付加 C. ベクターストアに投げる質問プロンプトの最適化 ⇒ 形態素またはキーワード抽出でプロンプトを精査 D. ベクターストア検索結果の精査 ⇒ ContextualCompressionRetriever による検索結果要約とDocumentCompressorPipeline による検索結果絞り込みがよさげ 「検索結果が質問に沿ったものか精査させる」タスクをChatGPTに担当してもらうことが私の業務課題には適しているのではという気付きがありました。 E. (おまけ)ベク

                        ChatGPT x LangChain で独自ドキュメントのベクターストア検索をチューニングする - GMOインターネットグループ グループ研究開発本部
                      • 0.10.0 Release Notes ⚡ The Zig Programming Language

                        Tier 4 Support § Support for these targets is entirely experimental. If this target is provided by LLVM, LLVM may have the target as an experimental target, which means that you need to use Zig-provided binaries for the target to be available, or build LLVM from source with special configure flags. zig targets will display the target if it is available. This target may be considered deprecated by

                        • prompts.chat - AI Prompts Community

                          --- name: skill-creator description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. license: Complete terms in LICENSE.txt --- # Skill Creator This skill provides guidance for creating effective skills. ## About Skills S

                            prompts.chat - AI Prompts Community
                          • Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers

                            For demonstration purposes, we'll fine-tune the multilingual version of the small checkpoint with 244M params (~= 1GB). As for our data, we'll train and evaluate our system on a low-resource language taken from the Common Voice dataset. We'll show that with as little as 8 hours of fine-tuning data, we can achieve strong performance in this language. 1{}^11 The name Whisper follows from the acronym

                              Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers
                            • What's New in Emacs 28.1?

                              Try Mastering Emacs for free! Are you struggling with the basics? Have you mastered movement and editing yet? When you have read Mastering Emacs you will understand Emacs. It’s that time again: there’s a new major version of Emacs and, with it, a treasure trove of new features and changes. Notable features include the formal inclusion of native compilation, a technique that will greatly speed up y

                              • OpenAssistant/oasst1 · Datasets at Hugging Face

                                'Jew' or 'rabbi'"},"role":{"kind":"string","value":"assistant"},"lang":{"kind":"string","value":"en"},"review_count":{"kind":"number","value":3,"string":"3"},"review_result":{"kind":"bool","value":true,"string":"true"},"deleted":{"kind":"bool","value":false,"string":"false"},"rank":{"kind":"number","value":1,"string":"1"},"synthetic":{"kind":"bool","value":false,"string":"false"},"model_name":{"ki

                                  OpenAssistant/oasst1 · Datasets at Hugging Face
                                • An Experienced (Neo)Vimmer's Workflow

                                  Motivation Ever since TJ said “Personalized Development Environment,” the phrase latched onto me like a cobweb in a mineshaft. A Personalized Development Environment (PDE) describes an ideal setup that is tailored to your needs and preferences – it lies between a bare-bone text editor and a full-fledged IDE. It is a place where you can be productive, efficient, and comfortable. It is a place that

                                  • LispText.pdf

                                    Lisp Common Lisp / Scheme 0.1 Copyright c � 2020, Katsunori Nakamura 2020 2 29 1 1 1.1 Common Lisp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.3.1 Lisp . . . . . .

                                    • Cognitive load is what matters

                                      The logo image was taken from Reddit. It is a living document, last update: May 2025. Your contributions are welcome! Introduction There are so many buzzwords and best practices out there, but most of them have failed. We need something more fundamental, something that can't be wrong. Sometimes we feel confusion going through the code. Confusion costs time and money. Confusion is caused by high co

                                        Cognitive load is what matters
                                      • NER(固有表現抽出)始めませんか? 第2回 | 株式会社NTTデータ先端技術

                                        CRFによる情報抽出サンプル 以下はこれら条件を元に、実際に抽出から精度評価までを行うコードです。 ※Pythonコードで記載しています import os from time import time import json from sklearn.metrics import make_scorer import sklearn_crfsuite from sklearn_crfsuite import metrics import joblib import numpy as np import fasttext def save_jsonl_file(file_name, jsonl): with open(file_name,"w", encoding="utf8") as f: for json_data in jsonl: json_text = json.dumps(jso

                                          NER(固有表現抽出)始めませんか? 第2回 | 株式会社NTTデータ先端技術
                                        • Python Dependency Injection

                                          Writing clean, maintainable code is a challenging task. Fortunately, there are many patterns, techniques, and reusable solutions available to us to make achieving that task much easier. Dependency Injection is one of those techniques, which is used to write loosely-coupled yet highly-cohesive code. In this article, we'll show you how to implement Dependency Injection as you develop an app for plot

                                            Python Dependency Injection
                                          • Cognitive load is what matters

                                            Last document update: October 2025. The logo image was taken from Reddit. This is a short version of the text. Toggle the switch to see a longer version. Prompt | Chinese | Japanese | Spanish | Korean | Turkish Introduction There are so many buzzwords and best practices out there, but most of them have failed. They failed because they were imagined, not real. These ideas were based on aesthetics a

                                              Cognitive load is what matters
                                            • A 'frozen' dictionary for Python

                                              Dictionaries are ubiquitous in Python code; they are the data structure of choice for a wide variety of tasks. But dictionaries are mutable, which makes them problematic for sharing data in concurrent code. Python has added various concurrency features to the language over the last decade or so—async, free threading without the global interpreter lock (GIL), and independent subinterpreters—but use

                                              • Django: what’s new in 6.0 - Adam Johnson

                                                Django 6.0 was released today, starting another release cycle for the loved and long-lived Python web framework (now 20 years old!). It comes with a mosaic of new features, contributed to by many, some of which I am happy to have helped with. Below is my pick of highlights from the release notes. Upgrade with help from django-upgrade If you’re upgrading a project from Django 5.2 or earlier, please

                                                • GitHub - ComfyUI-Workflow/awesome-comfyui: A collection of awesome custom nodes for ComfyUI

                                                  ComfyUI-Gemini_Flash_2.0_Exp (⭐+172): A ComfyUI custom node that integrates Google's Gemini Flash 2.0 Experimental model, enabling multimodal analysis of text, images, video frames, and audio directly within ComfyUI workflows. ComfyUI-ACE_Plus (⭐+115): Custom nodes for various visual generation and editing tasks using ACE_Plus FFT Model. ComfyUI-Manager (⭐+113): ComfyUI-Manager itself is also a cu

                                                    GitHub - ComfyUI-Workflow/awesome-comfyui: A collection of awesome custom nodes for ComfyUI
                                                  • Django for Startup Founders: A better software architecture for SaaS startups and consumer apps

                                                    In an ideal world, startups would be easy. We'd run our idea by some potential customers, build the product, and then immediately ride that sweet exponential growth curve off into early retirement. Of course it doesn't actually work like that. Not even a little. In real life, even startups that go on to become billion-dollar companies typically go through phases like: Having little or no growth fo

                                                    1