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| <!--1at4a0u--><meta name="hf:doc:metadata" content="{"title":"Quickstart","local":"quickstart","sections":[{"title":"Agent prompt","local":"agent-prompt","sections":[],"depth":2},{"title":"DiffusionPipeline","local":"diffusionpipeline","sections":[],"depth":2},{"title":"LoRA","local":"lora","sections":[],"depth":2},{"title":"Quantization and optimizations","local":"quantization-and-optimizations","sections":[],"depth":2},{"title":"Next steps","local":"next-steps","sections":[],"depth":2}],"depth":1}"/><!----> | |
| <link href="/docs/diffusers/main/en/_app/immutable/assets/0.tn0RQdqM.css" rel="modulepreload"> <!--[--><!--[0--><!--[--><!--[0--><!--[--><p></p> <div class="items-center shrink-0 min-w-[100px] max-sm:min-w-[50px] justify-end ml-auto flex" style="float: inline-end; margin-inline-start: 10px; display: inline-flex; position: relative; z-index: 10;"><div dir="ltr" class="inline-flex rounded-md max-sm:rounded-sm"><button class="inline-flex items-center gap-1 h-7 max-sm:h-7 px-2 max-sm:px-1.5 text-sm font-medium text-gray-800 border border-r-0 rounded-l-md max-sm:rounded-l-sm border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-live="polite"><span class="inline-flex items-center justify-center rounded-md p-0.5 max-sm:p-0 hover:text-gray-800 dark:hover:text-gray-200"><svg class="sm:size-3.5 size-3" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----></span> <span dir="auto">Copy page</span></button> <button class="inline-flex items-center justify-center w-6 max-sm:w-5 h-7 max-sm:h-7 disabled:pointer-events-none text-sm text-gray-500 hover:text-gray-700 dark:hover:text-white rounded-r-md max-sm:rounded-r-sm border border-l transition border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-haspopup="menu" aria-expanded="false" aria-label="Open copy menu"><svg class="transition-transform text-gray-400 overflow-visible sm:size-3.5 size-3 rotate-0" width="1em" height="1em" viewBox="0 0 12 7" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M1 1L6 6L11 1" stroke="currentColor"></path></svg><!----></button></div> <!--[-1--><!--]--></div><!----> <!--[0--><h1 class="relative group"><a id="quickstart" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#quickstart"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Introducción<!----></span></h1><!--]--><!----> <p>Diffusers es una biblioteca para desarrolladores e investigadores que proporciona una API de inferencia sencilla para generar imágenes, videos y audio, así como los bloques de construcción para implementar nuevos flujos de trabajo.</p> <p>Diffusers ofrece muchas optimizaciones de serie que permiten cargar y ejecutar modelos grandes en configuraciones con memoria limitada o acelerar la inferencia.</p> <p>Este tutorial de iniciación te dará una visión general de Diffusers y te permitirá empezar a generar contenido rápidamente.</p> <blockquote class="tip"><p>Antes de comenzar, asegúrate de tener una <a href="https://huggingface.co/join" rel="nofollow">cuenta</a> de Hugging Face para usar modelos con acceso restringido como <a href="https://huggingface.co/black-forest-labs/FLUX.1-dev" rel="nofollow">Flux</a>. ¿Prefieres construir un pipeline personalizado? Consulta la <a href="./modular_diffusers/quickstart">introducción rápida a Modular Diffusers</a> y el <a href="./modular_diffusers/overview">resumen</a>.</p></blockquote> <p>Sigue la guía de <a href="./installation">Instalación</a> para instalar Diffusers si aún no está instalado.</p> <!--[1--><h2 class="relative group"><a id="agent-prompt" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#agent-prompt"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Prompt del agente<!----></span></h2><!--]--><!----> <p>Pega esto en tu agente de codificación para configurar Diffusers para inferencia.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-text "><!---->Help me get set up with Hugging Face Diffusers for inference. | |
| 1. Install Diffusers for my environment with `uv pip install "diffusers[torch]"`. | |
| 2. If I need gated Hub models, help me authenticate to the Hugging Face Hub. | |
| 3. Install Diffusers coding agent skills with `diffusers-cli skills add diffusers-cli`. Pass `--cursor`, `--claude`, or `--codex` if auto-detect fails. Optionally pass `--all` to install every skill in the registry. | |
| 4. Run a first text-to-image with DiffusionPipeline or `diffusers-cli run`, using a small or current Quickstart model and the right `device_map` for my machine. | |
| 5. Ask what I want next and point me at the matching docs.<!----></pre></div><!----> <!--[1--><h2 class="relative group"><a id="diffusionpipeline" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#diffusionpipeline"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->DiffusionPipeline<!----></span></h2><!--]--><!----> <p><a href="/docs/diffusers/main/es/api/pipelines/overview#diffusers.DiffusionPipeline">DiffusionPipeline</a> agrupa los componentes de un modelo de difusión (codificador de texto, programador, UNet o DiT y VAE) en una sola clase para la inferencia. Cargue con <a href="/docs/diffusers/main/es/api/pipelines/overview#diffusers.DiffusionPipeline.from_pretrained">from_pretrained()</a> y luego llame a la tubería.</p> <p>Los argumentos de <code>__call__()</code> como <code>num_inference_steps</code> cambian la calidad y la velocidad. Para ver los detalles de carga y los componentes combinables, consulte <a href="./using-diffusers/loading">Cargar pipelines</a>. Para cambiar el programador, consulte <a href="./using-diffusers/schedulers">Programadores</a>.</p> <p>Los ejemplos a continuación utilizan los valores de argumento predeterminados.</p> <div class="flex space-x-2 items-center my-1.5 mr-8 h-7 !pl-0 -mx-3 md:mx-0"><!--[--><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd border-gray-800 bg-black dark:bg-gray-700 text-white">texto a imagen</div><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd text-gray-500 cursor-pointer opacity-90 hover:text-gray-700 dark:hover:text-gray-200 hover:shadow-sm">texto a video</div><!--]--></div> <div class="language-select"><div><p>Use <code>.images[0]</code> para acceder a la imagen generada.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| <span class="hljs-string">"Qwen/Qwen-Image"</span>, dtype=torch.bfloat16, device_map=<span class="hljs-string">"cuda"</span> <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| ) | |
| prompt = <span class="hljs-string">""" | |
| cinematic film still of a cat sipping a margarita in a pool in Palm Springs, California | |
| highly detailed, high budget hollywood movie, cinemascope, moody, epic, gorgeous, film grain | |
| """</span> | |
| pipeline(prompt).images[<span class="hljs-number">0</span>]<!----></pre></div><!----><!----></div><!----> <div hidden=""><p>Use <code>.frames[0]</code> para acceder a la salida del video generado y <a href="/docs/diffusers/main/es/api/utilities#diffusers.utils.export_to_video">export_to_video()</a> para guardar el video.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoencoderKLWan, DiffusionPipeline | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> export_to_video | |
| vae = AutoencoderKLWan.from_pretrained( | |
| <span class="hljs-string">"Wan-AI/Wan2.2-T2V-A14B-Diffusers"</span>, | |
| subfolder=<span class="hljs-string">"vae"</span>, | |
| dtype=torch.float32 | |
| ) | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| <span class="hljs-string">"Wan-AI/Wan2.2-T2V-A14B-Diffusers"</span>, | |
| vae=vae, | |
| dtype=torch.bfloat16, | |
| device_map=<span class="hljs-string">"cuda"</span> <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| ) | |
| prompt = <span class="hljs-string">""" | |
| Cinematic video of a sleek cat lounging on a colorful inflatable in a crystal-clear turquoise pool in Palm Springs, | |
| sipping a salt-rimmed margarita through a straw. Golden-hour sunlight glows over mid-century modern homes and swaying palms. | |
| Shot in rich Sony a7S III: with moody, glamorous color grading, subtle lens flares, and soft vintage film grain. | |
| Ripples shimmer as a warm desert breeze stirs the water, blending luxury and playful charm in an epic, gorgeously composed frame. | |
| """</span> | |
| video = pipeline(prompt=prompt, num_frames=<span class="hljs-number">81</span>, num_inference_steps=<span class="hljs-number">40</span>).frames[<span class="hljs-number">0</span>] | |
| export_to_video(video, <span class="hljs-string">"output.mp4"</span>, fps=<span class="hljs-number">16</span>)<!----></pre></div><!----><!----></div><!----><!----></div><!----> <!--[1--><h2 class="relative group"><a id="lora" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#lora"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->LoRA<!----></span></h2><!--]--><!----> <p>Los adaptadores <a href="./tutorials/using_peft_for_inference">LoRA</a> añaden un punto de control de estilo o sujeto pequeño sobre un pipeline base. Carga uno con <a href="/docs/diffusers/main/es/api/loaders/lora#diffusers.loaders.QwenImageLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>. Algunos LoRA requieren una frase de activación. Consulta la tarjeta de modelo del LoRA.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| <span class="hljs-string">"Qwen/Qwen-Image"</span>, dtype=torch.bfloat16, device_map=<span class="hljs-string">"cuda"</span> <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| ) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"threecrowco/VolkClipartQwen"</span>, | |
| weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, | |
| ) | |
| prompt = <span class="hljs-string">""" | |
| Volk clipart style drawing of a cat sipping a margarita in a pool in Palm Springs, California, flat colors, bold outlines, simple shapes | |
| """</span> | |
| pipeline(prompt).images[<span class="hljs-number">0</span>]<!----></pre></div><!----> <!--[1--><h2 class="relative group"><a id="quantization-and-optimizations" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#quantization-and-optimizations"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Cuantización y optimizaciones<!----></span></h2><!--]--><!----> <p>Los modelos grandes a menudo requieren menos memoria o más velocidad. Utilice <a href="./quantization/overview">cuantización</a> para reducir los pesos en memoria y <a href="/docs/diffusers/main/es/api/models/overview#diffusers.ModelMixin.compile_repeated_blocks">compile_repeated_blocks()</a> para acelerar las generaciones posteriores. Para <a href="./optimization/memory#model-offloading">descarga de modelos</a> y otras opciones, consulte <a href="./optimization/overview">Optimizar y escalar</a>.</p> <p>Para usar menos memoria, cargue en 4 bits con bitsandbytes.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline | |
| <span class="hljs-keyword">from</span> diffusers.quantizers <span class="hljs-keyword">import</span> PipelineQuantizationConfig | |
| quant_config = PipelineQuantizationConfig( | |
| quant_backend=<span class="hljs-string">"bitsandbytes_4bit"</span>, | |
| quant_kwargs={<span class="hljs-string">"load_in_4bit"</span>: <span class="hljs-literal">True</span>, <span class="hljs-string">"bnb_4bit_quant_type"</span>: <span class="hljs-string">"nf4"</span>, <span class="hljs-string">"bnb_4bit_compute_dtype"</span>: torch.bfloat16}, | |
| components_to_quantize=[<span class="hljs-string">"transformer"</span>, <span class="hljs-string">"text_encoder"</span>], | |
| ) | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| <span class="hljs-string">"Qwen/Qwen-Image"</span>, | |
| dtype=torch.bfloat16, | |
| quantization_config=quant_config, | |
| device_map=<span class="hljs-string">"cuda"</span> <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| ) | |
| prompt = <span class="hljs-string">""" | |
| cinematic film still of a cat sipping a margarita in a pool in Palm Springs, California | |
| highly detailed, high budget hollywood movie, cinemascope, moody, epic, gorgeous, film grain | |
| """</span> | |
| pipeline(prompt).images[<span class="hljs-number">0</span>]<!----></pre></div><!----> <p>Para acelerar las ejecuciones posteriores, compile los bloques repetidos del transformer. El primer generate después de la compilación es un arranque en frío y es lento. Los generates posteriores son más rápidos.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| <span class="hljs-string">"Qwen/Qwen-Image"</span>, dtype=torch.bfloat16, device_map=<span class="hljs-string">"cuda"</span> <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| ) | |
| pipeline.transformer.compile_repeated_blocks(fullgraph=<span class="hljs-literal">True</span>) | |
| prompt = <span class="hljs-string">""" | |
| cinematic film still of a cat sipping a margarita in a pool in Palm Springs, California | |
| highly detailed, high budget hollywood movie, cinemascope, moody, epic, gorgeous, film grain | |
| """</span> | |
| pipeline(prompt).images[<span class="hljs-number">0</span>]<!----></pre></div><!----> <!--[1--><h2 class="relative group"><a id="next-steps" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#next-steps"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Próximos pasos<!----></span></h2><!--]--><!----> <ul><li><a href="./using-diffusers/loading">Inferencia</a> — pipelines, prompting y adaptadores</li> <li><a href="./optimization/overview">Optimizar y escalar</a> — memoria, velocidad, cuantización y servicio</li> <li><a href="./modular_diffusers/overview">Diffusers modulares</a> — bloques componibles y pipelines personalizados</li> <li><a href="./training/overview">Entrenar y ajustar</a> — scripts de entrenamiento y adaptadores</li> <li><a href="./using-diffusers/cli">CLI</a> — generar desde la línea de comandos</li></ul> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/diffusers/blob/main/docs/source/en/quicktour.md" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg><!----> <span><span class="underline">Update</span> on GitHub</span></a><!----> <p></p><!--]--><!----><!--]--><!--]--><!--]--> <!--[-1--><!--]--><!--]--> | |
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