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How are documents usually evaluated in the simplest form of keyword-based search? According to the length of the documents Based on the number of images and videos contained in the documents By the complexity of language used in the documents ** Based on the presence and frequency of the user-provided keywords

When is fine-tuning an appropriate method for customizing a Large Language Model (LLM)? When you want to optimize the model without any instructions When the LLM requires access to the latest data for generating outputs ** When the LLM does not perform well on a task and the data for prompt engineering is too large

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Curso Docker - Guía práctica de uso para desarrolladores

1. Node JS

2. VSCode - Visual Studio Code

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Instalación y configuracion de Jest + React Testing Library

En proyectos de React + Vite

1. Instalaciones:

yarn add --dev jest babel-jest @babel/preset-env @babel/preset-react 
yarn add --dev @testing-library/react @types/jest jest-environment-jsdom

2. Opcional: Si usamos Fetch API en el proyecto:

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import { ObjectId } from "bson"

let movies
let mflix
const DEFAULT_SORT = [["tomatoes.viewer.numReviews", -1]]

export default class MoviesDAO {
  static async injectDB(conn) {
    if (movies) {
      return

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Bootstrap 3 - Carousel/Slider Collection

Article: http://sevenx.de/blog
Demo: http://sevenx.de/demo/bootstrap-carousel

Working Examples (inline Styles, CDN Scripts)

- minimal Bootstrap Markup changes
- minimal CSS Styles
- minimal jQuery