<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Google Colaboratory on kenji.blog</title><link>http://kenji.blog/es/tags/google-colaboratory/</link><description>Recent content in Google Colaboratory on kenji.blog</description><generator>Hugo -- gohugo.io</generator><language>es</language><copyright>kenjinote</copyright><lastBuildDate>Sun, 09 Apr 2023 01:02:19 +0900</lastBuildDate><atom:link href="http://kenji.blog/es/tags/google-colaboratory/index.xml" rel="self" type="application/rss+xml"/><item><title>Cómo dibujar un gráfico usando Python (matplotlib.pyplot)</title><link>http://kenji.blog/es/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/</link><pubDate>Sun, 09 Apr 2023 01:02:19 +0900</pubDate><guid>http://kenji.blog/es/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/</guid><description>&lt;img src="http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img.png" alt="Featured image of post Cómo dibujar un gráfico usando Python (matplotlib.pyplot)" />&lt;p>&lt;img src="http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1.png"
width="1200"
height="288"
srcset="http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1_hue3f23818eeeec9c43d6452cc0f61fb52_43864_480x0_resize_box_3.png 480w, http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1_hue3f23818eeeec9c43d6452cc0f61fb52_43864_1024x0_resize_box_3.png 1024w"
loading="lazy"
alt="img_1.png"
class="gallery-image"
data-flex-grow="416"
data-flex-basis="1000px"
>&lt;/p>
&lt;h1 id="requisitos">Requisitos
&lt;/h1>&lt;ul>
&lt;li>Cuenta de Google&lt;/li>
&lt;/ul>
&lt;h1 id="procedimiento">Procedimiento
&lt;/h1>&lt;ol>
&lt;li>Accede a &lt;a class="link" href="https://colab.research.google.com/" target="_blank" rel="noopener"
>https://colab.research.google.com/&lt;/a>&lt;/li>
&lt;li>Selecciona &amp;ldquo;Archivo&amp;rdquo; → &amp;ldquo;Nuevo cuaderno&amp;rdquo;&lt;/li>
&lt;li>Pega y ejecuta el siguiente código:&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;span class="lnt">2
&lt;/span>&lt;span class="lnt">3
&lt;/span>&lt;span class="lnt">4
&lt;/span>&lt;span class="lnt">5
&lt;/span>&lt;span class="lnt">6
&lt;/span>&lt;span class="lnt">7
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-python" data-lang="python">&lt;span class="line">&lt;span class="cl">&lt;span class="kn">import&lt;/span> &lt;span class="nn">matplotlib.pyplot&lt;/span> &lt;span class="k">as&lt;/span> &lt;span class="nn">plt&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="kn">import&lt;/span> &lt;span class="nn">numpy&lt;/span> &lt;span class="k">as&lt;/span> &lt;span class="nn">np&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">x&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="n">np&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">linspace&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="mi">0&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="mi">2&lt;/span>&lt;span class="o">*&lt;/span>&lt;span class="n">np&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">pi&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="mi">500&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">plt&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">plot&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">x&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">np&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">sin&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">x&lt;/span>&lt;span class="p">),&lt;/span> &lt;span class="n">label&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="s2">&amp;#34;sin curve&amp;#34;&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">plt&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">plot&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">x&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">np&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">cos&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">x&lt;/span>&lt;span class="p">),&lt;/span> &lt;span class="n">label&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="s2">&amp;#34;cos curve&amp;#34;&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">plt&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">legend&lt;/span>&lt;span class="p">()&lt;/span> &lt;span class="c1"># Muestra la leyenda&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">plt&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">show&lt;/span>&lt;span class="p">()&lt;/span>
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;h1 id="resultado-de-la-ejecución">Resultado de la ejecución
&lt;/h1>&lt;p>&lt;img src="http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img.png"
width="568"
height="413"
srcset="http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_hucdb24ab588d845f9f7a56ef99be2c709_27745_480x0_resize_box_3.png 480w, http://kenji.blog/p/pythonmatplotlib.pyplot%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%B0%E3%83%A9%E3%83%95%E3%82%92%E6%8F%8F%E7%94%BB%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_hucdb24ab588d845f9f7a56ef99be2c709_27745_1024x0_resize_box_3.png 1024w"
loading="lazy"
alt="img.png"
class="gallery-image"
data-flex-grow="137"
data-flex-basis="330px"
>&lt;/p>
&lt;h1 id="referencias">Referencias
&lt;/h1>&lt;ul>
&lt;li>&lt;a class="link" href="https://matplotlib.org/3.5.3/api/_as_gen/matplotlib.pyplot.html" target="_blank" rel="noopener"
>matplotlib.pyplot — Matplotlib 3.5.3 documentation&lt;/a>&lt;/li>
&lt;/ul></description></item><item><title>Cómo tuitear usando la API de Twitter y Google Colaboratory</title><link>http://kenji.blog/es/p/twitter-api%E3%81%A8google-colaboratory%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6tweet%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/</link><pubDate>Sat, 08 Apr 2023 18:48:32 +0900</pubDate><guid>http://kenji.blog/es/p/twitter-api%E3%81%A8google-colaboratory%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6tweet%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/</guid><description>&lt;img src="http://kenji.blog/p/twitter-api%E3%81%A8google-colaboratory%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6tweet%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img.png" alt="Featured image of post Cómo tuitear usando la API de Twitter y Google Colaboratory" />&lt;h1 id="lo-que-necesitas">Lo que necesitas
&lt;/h1>&lt;ul>
&lt;li>API de Twitter&lt;/li>
&lt;li>Twitter API SECRET&lt;/li>
&lt;li>Twitter ACCESS TOKEN&lt;/li>
&lt;li>Twitter ACCESS TOKEN SECRET&lt;/li>
&lt;li>Cuenta de Google&lt;/li>
&lt;/ul>
&lt;p>Para obtener la API de Twitter, consulta los sitios de referencia.&lt;/p>
&lt;h1 id="procedimiento-para-tuitear-usando-la-api">Procedimiento para tuitear usando la API
&lt;/h1>&lt;ol>
&lt;li>Accede a &lt;a class="link" href="https://colab.research.google.com/" target="_blank" rel="noopener"
>https://colab.research.google.com/&lt;/a>&lt;/li>
&lt;li>Selecciona &amp;ldquo;Archivo&amp;rdquo; → &amp;ldquo;Nuevo cuaderno&amp;rdquo;&lt;/li>
&lt;li>Pega y ejecuta el siguiente código (usa los valores reales que obtuviste)&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;span class="lnt">2
&lt;/span>&lt;span class="lnt">3
&lt;/span>&lt;span class="lnt">4
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-python" data-lang="python">&lt;span class="line">&lt;span class="cl">&lt;span class="n">API_KEY&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="s1">&amp;#39;9Smu2f2RoLqbVQHQq6n79Z2JW&amp;#39;&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">API_SECRET&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="s1">&amp;#39;uGVRIkLL2l8sRyPv2Lr4mXxXppnQF1isMoRnvktcXCtFgAK2R8&amp;#39;&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">ACCESS_TOKEN&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="s1">&amp;#39;0367292979164670705-7hSErDoQbO6fkFtnn5UY0vqpvecy0O&amp;#39;&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">ACCESS_TOKEN_SECRET&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="s1">&amp;#39;pUv81U9GVzZirz5g4AxZPHAJ4GpSXnBo8GUcZ1egtjw9q&amp;#39;&lt;/span>
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;ol start="3">
&lt;li>Pega y ejecuta el siguiente código&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-python" data-lang="python">&lt;span class="line">&lt;span class="cl">&lt;span class="kn">import&lt;/span> &lt;span class="nn">tweepy&lt;/span>
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;ol start="4">
&lt;li>Pega y ejecuta el siguiente código (API v1.1)&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;span class="lnt">2
&lt;/span>&lt;span class="lnt">3
&lt;/span>&lt;span class="lnt">4
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-python" data-lang="python">&lt;span class="line">&lt;span class="cl">&lt;span class="n">auth&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="n">tweepy&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">OAuthHandler&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">API_KEY&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">API_SECRET&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">auth&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">set_access_token&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">ACCESS_TOKEN&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">ACCESS_TOKEN_SECRET&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">api&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="n">tweepy&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">API&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">auth&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">api&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">update_status&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="s2">&amp;#34;hello&amp;#34;&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;p>→ Se publicará el tuit &lt;code>hello&lt;/code>&lt;/p>
&lt;ol start="5">
&lt;li>Pega y ejecuta el siguiente código (API v2.0)&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;span class="lnt">2
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-python" data-lang="python">&lt;span class="line">&lt;span class="cl">&lt;span class="n">client&lt;/span> &lt;span class="o">=&lt;/span> &lt;span class="n">tweepy&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">Client&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">consumer_key&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="n">API_KEY&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">consumer_secret&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="n">API_SECRET&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">access_token&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="n">ACCESS_TOKEN&lt;/span>&lt;span class="p">,&lt;/span> &lt;span class="n">access_token_secret&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="n">ACCESS_TOKEN_SECRET&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">&lt;span class="n">client&lt;/span>&lt;span class="o">.&lt;/span>&lt;span class="n">create_tweet&lt;/span>&lt;span class="p">(&lt;/span>&lt;span class="n">text&lt;/span>&lt;span class="o">=&lt;/span>&lt;span class="s1">&amp;#39;hello v2&amp;#39;&lt;/span>&lt;span class="p">)&lt;/span>
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;p>→ Se publicará el tuit &lt;code>hello v2&lt;/code>&lt;/p>
&lt;p>Eso es todo.&lt;/p>
&lt;h1 id="referencias">Referencias
&lt;/h1>&lt;ul>
&lt;li>&lt;a class="link" href="https://bloomtectec.com/twitter-api-application-procedure/" target="_blank" rel="noopener"
>【A partir de abril de 2021】Explicación exhaustiva del procedimiento de solicitud de la API de Twitter con ejemplos de uso y capturas de pantalla&lt;/a>&lt;/li>
&lt;li>&lt;a class="link" href="https://bloomtectec.com/use-twitter-api-in-google-colab/" target="_blank" rel="noopener"
>【¡Sin configuraciones molestas!】Google Colaboratory es recomendado para probar la API de Twitter 【También compartimos el código fuente】&lt;/a>&lt;/li>
&lt;li>&lt;a class="link" href="https://3pysci.com/tweepy-28/" target="_blank" rel="noopener"
>【Tweepy】Twitter API v2: Tuitear, responder (reply), tuits con encuesta, tuits con medios (v1.1) [Python]&lt;/a>&lt;/li>
&lt;/ul></description></item><item><title>Cómo generar imágenes de ilustraciones usando IA (Stable Diffusion)</title><link>http://kenji.blog/es/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/</link><pubDate>Thu, 06 Apr 2023 00:43:19 +0900</pubDate><guid>http://kenji.blog/es/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/</guid><description>&lt;img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img.png" alt="Featured image of post Cómo generar imágenes de ilustraciones usando IA (Stable Diffusion)" />&lt;h1 id="qué-es-stable-diffusion">¿Qué es Stable Diffusion?
&lt;/h1>&lt;p>Stable Diffusion es una IA que genera imágenes a partir de información de texto (texto a imagen), desarrollada por un equipo de investigación de la Universidad de Múnich, Alemania.
Al entrenar con diversas imágenes, puede generar una amplia variedad de imágenes, desde fotografías realistas hasta ilustraciones.&lt;/p>
&lt;p>En esta ocasión, presentaré cómo generar imágenes de ilustraciones utilizando datos preentrenados de Stable Diffusion.&lt;/p>
&lt;h1 id="lo-que-necesitas">Lo que necesitas
&lt;/h1>&lt;ul>
&lt;li>Una cuenta de Google&lt;/li>
&lt;/ul>
&lt;p>Solo eso.&lt;/p>
&lt;h1 id="procedimiento-de-generación">Procedimiento de generación
&lt;/h1>&lt;ol>
&lt;li>Abre &lt;a class="link" href="https://colab.research.google.com" target="_blank" rel="noopener"
>https://colab.research.google.com&lt;/a>&lt;/li>
&lt;li>En la esquina superior izquierda, selecciona &lt;code>Archivo&lt;/code> y luego &lt;code>Nuevo cuaderno&lt;/code>&lt;/li>
&lt;li>Selecciona &lt;code>Editar&lt;/code> y luego &lt;code>Configuración del cuaderno&lt;/code>&lt;/li>
&lt;li>Cambia el &lt;code>Acelerador de hardware&lt;/code> a &lt;code>GPU&lt;/code>
&lt;img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_2.png"
width="627"
height="324"
srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_2_hud7bbdf6a24e33b2b36528d9e25b016c8_23961_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_2_hud7bbdf6a24e33b2b36528d9e25b016c8_23961_1024x0_resize_box_3.png 1024w"
loading="lazy"
alt="img_2.png"
class="gallery-image"
data-flex-grow="193"
data-flex-basis="464px"
>&lt;/li>
&lt;li>Pega y ejecuta el siguiente código&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-fallback" data-lang="fallback">&lt;span class="line">&lt;span class="cl">!pip install diffusers==0.8.0 transformers
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;ol start="6">
&lt;li>Pega y ejecuta el siguiente código&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-fallback" data-lang="fallback">&lt;span class="line">&lt;span class="cl">from diffusers import StableDiffusionPipeline
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;ol start="7">
&lt;li>Pega y ejecuta el siguiente código&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;span class="lnt">2
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-fallback" data-lang="fallback">&lt;span class="line">&lt;span class="cl">pipe = StableDiffusionPipeline.from_pretrained(&amp;#34;gsdf/Counterfeit-V2.5&amp;#34;)
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">pipe.to(&amp;#34;cuda&amp;#34;)
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;ol start="8">
&lt;li>Pega y ejecuta el siguiente código&lt;/li>
&lt;/ol>
&lt;div class="highlight">&lt;div class="chroma">
&lt;table class="lntable">&lt;tr>&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code>&lt;span class="lnt">1
&lt;/span>&lt;span class="lnt">2
&lt;/span>&lt;span class="lnt">3
&lt;/span>&lt;span class="lnt">4
&lt;/span>&lt;span class="lnt">5
&lt;/span>&lt;/code>&lt;/pre>&lt;/td>
&lt;td class="lntd">
&lt;pre tabindex="0" class="chroma">&lt;code class="language-fallback" data-lang="fallback">&lt;span class="line">&lt;span class="cl">prompt = &amp;#34;((masterpiece,best quality)),1girl, solo, animal ears, rabbit, barefoot, knees up, dress, sitting, rabbit ears, short sleeves, looking at viewer, grass, short hair, smile, white hair, puffy sleeves, outdoors, puffy short sleeves, bangs, on ground, full body, animal, white dress, sunlight, brown eyes, dappled sunlight, day, depth of field&amp;#34;
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">n_prompt = &amp;#34;EasyNegative, extra fingers,fewer fingers&amp;#34;
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">image = pipe(prompt, negative_prompt = n_prompt).images[0]
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">image
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/td>&lt;/tr>&lt;/table>
&lt;/div>
&lt;/div>&lt;p>El &lt;code>Prompt&lt;/code> utilizado aquí está basado en el &lt;code>Prompt&lt;/code> de &lt;a class="link" href="https://huggingface.co/gsdf/Counterfeit-V2.5" target="_blank" rel="noopener"
>https://huggingface.co/gsdf/Counterfeit-V2.5&lt;/a>.&lt;/p>
&lt;h2 id="resultados-generados-algunos">Resultados generados (algunos)
&lt;/h2>&lt;p>&lt;img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1.png"
width="512"
height="512"
srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1_hu1ec19e515fd7538067cc14f2c3c8bddf_594392_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1_hu1ec19e515fd7538067cc14f2c3c8bddf_594392_1024x0_resize_box_3.png 1024w"
loading="lazy"
alt="img_1.png"
class="gallery-image"
data-flex-grow="100"
data-flex-basis="240px"
>&lt;/p>
&lt;p>&lt;img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_3.png"
width="512"
height="512"
srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_3_hu67e673668e1b02812ead4fb15912ac36_533749_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_3_hu67e673668e1b02812ead4fb15912ac36_533749_1024x0_resize_box_3.png 1024w"
loading="lazy"
alt="img_3.png"
class="gallery-image"
data-flex-grow="100"
data-flex-basis="240px"
>&lt;/p>
&lt;p>&lt;img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_4.png"
width="512"
height="512"
srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_4_hu2b826ec3ad4d7685d995efaa40aac0c5_597506_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_4_hu2b826ec3ad4d7685d995efaa40aac0c5_597506_1024x0_resize_box_3.png 1024w"
loading="lazy"
alt="img_4.png"
class="gallery-image"
data-flex-grow="100"
data-flex-basis="240px"
>&lt;/p>
&lt;h2 id="referencias">Referencias
&lt;/h2>&lt;ul>
&lt;li>&lt;a class="link" href="https://huggingface.co/gsdf/Counterfeit-V2.5" target="_blank" rel="noopener"
>https://huggingface.co/gsdf/Counterfeit-V2.5&lt;/a>&lt;/li>
&lt;li>&lt;a class="link" href="https://www.youtube.com/watch?v=l8-fVSM2PVQ" target="_blank" rel="noopener"
>Hice un programa de generación de imágenes con Inteligencia Artificial (IA) en 15 minutos 【Programación en vivo】&lt;/a>&lt;/li>
&lt;/ul></description></item></channel></rss>