- \n
- Revisi\u00f3n jur\u00eddica y de conformidad<\/li>\n
- Automatizaci\u00f3n de la atenci\u00f3n al cliente<\/li>\n
- Soluci\u00f3n de problemas t\u00e9cnicos<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
Para esta demostraci\u00f3n, utilizaremos DeepSeek Distill-Llama-3-8B<\/a>, pero Capella AI Services en GA planea introducir variantes de mayor par\u00e1metro del modelo para ampliar a\u00fan m\u00e1s sus capacidades.<\/p>\n
\ud83d\ude80 \u00bfLe interesa probar DeepSeek-R1?<\/b> Echa un vistazo Servicios de IA de Capella<\/a> o Inscr\u00edbase en el Vista previa privada<\/a>.<\/p>\n
Comprender el modelo DeepSeek<\/h2>\n
Enfoque de destilaci\u00f3n<\/h3>\n
DeepSeek Distill-Llama-3-8B<\/a> se entrena con destilaci\u00f3n de conocimientos<\/b>donde a modelo de profesor m\u00e1s grande (DeepSeek-R1)<\/b> orienta la formaci\u00f3n de un modelo de estudiante m\u00e1s peque\u00f1o y eficiente (Llama 3 8B)<\/b>. El resultado es un modelo compacto pero potente<\/b> que conserva una gran capacidad de razonamiento al tiempo que reduce los costes computacionales.<\/p>\n
\nConjunto de datos: evaluaci\u00f3n comparativa con BEIR<\/h2>\n
Estamos evaluando las capacidades de razonamiento del modelo utilizando el Conjunto de datos BEIR<\/b><\/a>un punto de referencia est\u00e1ndar para razonamiento basado en la recuperaci\u00f3n<\/b>. El conjunto de datos consta de 75K documentos<\/b> en varios \u00e1mbitos, estructurados del siguiente modo:<\/p>\n
{\r\n\u00a0\u00a0\u00a0\u00a0\"_id\": \"632589828c8b9fca2c3a59e97451fde8fa7d188d\",\r\n\u00a0\u00a0\u00a0\u00a0\"title\": \"A hybrid of genetic algorithm and particle swarm optimization for recurrent network design\",\r\n\u00a0\u00a0\u00a0\u00a0\"text\": \"An evolutionary recurrent network which automates the design of recurrent neural\/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper...\",\r\n\u00a0\u00a0\u00a0\u00a0\"query\": \"what is gappso?\"\r\n}<\/pre>\nLa capacidad del modelo se comprueba determinando qu\u00e9 documentos contienen las respuestas correctas a determinadas consultas<\/b>demostrando su fuerza de razonamiento.<\/p>\n
Primeros pasos: implantaci\u00f3n de DeepSeek en Capella AI Services<\/h2>\n
Paso 1: Ingesta de documentos<\/h3>\n
Ahora puede generar incrustaciones vectoriales para documentos estructurados y no estructurados utilizando los servicios de Capella AI. En primer lugar, vamos a importar los documentos estructurados del conjunto de datos BEIR en una colecci\u00f3n couchbase antes de desplegar un flujo de trabajo de vectorizaci\u00f3n.<\/p>\n
Configura un cl\u00faster de base de datos operativo de 5 nodos (\u00a1o m\u00e1s grande!) en Couchbase Capella con las funciones de b\u00fasqueda y eventos habilitadas. Puedes aprovechar una opci\u00f3n de despliegue multinodo preconfigurada o crear una configuraci\u00f3n personalizada.<\/p>\n
![\"Node](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image12-1024x455.png\")
<\/a><\/p>\nUna vez desplegado el cl\u00faster, dir\u00edjase a la secci\u00f3n Importar<\/strong> en la pesta\u00f1a Herramientas de datos<\/strong> y haga clic en la opci\u00f3n de importaci\u00f3n. Para grandes conjuntos de datos, puede utilizar la opci\u00f3n cb-import<\/em> funci\u00f3n.<\/p>\n
![\"NoSQL](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image13-1024x430.png\")
<\/a>Configure un bucket, scope y collection adicionales en su cluster operativo. Lo utilizaremos m\u00e1s adelante como almac\u00e9n para la cach\u00e9 conversacional.<\/p>\n![\"NoSQL](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image10-1024x522.png\")
<\/a><\/p>\nPaso 2: Establecer un modelo de incrustaci\u00f3n<\/h3>\n
Vuelve a la pesta\u00f1a de modelos en la pesta\u00f1a de servicios de Capella AI. Haga clic en el bot\u00f3n Modelo de servicio<\/strong> antes de seleccionar las siguientes opciones:<\/p>\n
![\"AI](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image1-1024x501.jpg\")
<\/a>![\"Choose](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image9-1024x761.png\")
<\/a><\/p>\nPaso 3: Configurar un flujo de trabajo de vectorizaci\u00f3n<\/h3>\n
Ahora que los documentos han sido ingestados, consulte este post para m\u00e1s detalles sobre c\u00f3mo desplegar un flujo de trabajo de vectorizaci\u00f3n.<\/p>\n
![\"Automated](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image4-1-1024x521.png\")
<\/a><\/p>\nAsigne un nombre a su flujo de trabajo y especifique la colecci\u00f3n que contiene los documentos ingestados.<\/p>\n
![\"Automated](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image8-1024x656.png\")
<\/a><\/p>\nSeleccione el modelo de incrustaci\u00f3n desplegado en el paso anterior.<\/p>\n
![\"Choose](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image2-2-1024x494.png\")
<\/a><\/p>\nEspecifique el nombre del campo en el que se insertar\u00e1n los vectores generados y el nombre del \u00edndice que se construir\u00e1 sobre \u00e9l:<\/p>\n
![\"Select](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image5-1-1024x609.png\")
<\/a><\/p>\nPaso 4: Configurar el modelo DeepSeek<\/h3>\n
Vuelve a la secci\u00f3n de servicios de Capella AI y haz clic en la pesta\u00f1a de modelos y haz clic en el bot\u00f3n Modelo de servicio<\/strong> antes de seleccionar las siguientes opciones:<\/p>\n
<\/a><\/p>\nSeleccione el cl\u00faster de base de datos operativa creado anteriormente en el men\u00fa desplegable, seleccione el Capella Peque\u00f1o<\/strong> y el modelo DeepSeek Distill-LLama-3-8B en el men\u00fa desplegable.<\/p>\n
![\"Select](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image3-2-1024x545.png\")
<\/a><\/p>\nConfigure la cach\u00e9 seleccionando un bucket-scope-collection y marcando la casilla Cach\u00e9 conversacional<\/strong> caja.<\/p>\n
![\"Cache](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image6-1-1024x534.jpg\")
<\/a><\/p>\nCrear una aplicaci\u00f3n con DeepSeek<\/h2>\n
Paso 1: Configurar los ajustes para que la aplicaci\u00f3n acceda a los datos<\/h3>\n
Aseg\u00farese de que su direcci\u00f3n IP est\u00e1 en la lista blanca para acceder a los documentos de su base de datos operativa. Para ello, vaya a la p\u00e1gina Conectar<\/strong>\u00a0del cl\u00faster operativo creado anteriormente.<\/p>\n
![\"Configure](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image7-1024x591.jpg\")
<\/a><\/p>\nPaso 2: Ejecutar la aplicaci\u00f3n<\/h3>\n
Utilice el ejemplo proporcionado aqu\u00ed<\/a> para configurar una aplicaci\u00f3n que recupere los documentos del conjunto de datos BEIR almacenados en su base de datos operativa y, a continuaci\u00f3n, genere una respuesta. Aseg\u00farese de especificar correctamente sus credenciales de base de datos codificadas en base64 y el punto final del modelo. Puede encontrar el punto final del modelo accediendo a la carpeta Servicios de IA -> Modelos<\/strong> y, a continuaci\u00f3n, haga clic en el bot\u00f3n de flecha hacia abajo, que mostrar\u00e1 la configuraci\u00f3n del modelo.<\/p>\n
![\"Manage](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2025\/02\/image11-1024x389.png\")
<\/a><\/p>\nPaso 3: Probar el DeepSeek-R1-Distill-Llama-8B<\/h3>\n
Env\u00ede una consulta de ejemplo al modelo y compruebe los resultados. Una vez que haya verificado la respuesta del modelo, puede ejecutar todo el conjunto de datos a trav\u00e9s del modelo.<\/p>\n
Pr\u00f3ximos pasos<\/h2>\n
- \n
- \n
- \n
- \ud83d\ude80 Acceso anticipado a DeepSeek-R1<\/b> - Inscribirse en la lista de espera<\/a><\/li>\n
- \ud83d\udcd6 M\u00e1s informaci\u00f3n sobre los modelos DeepSeek<\/b> - Documento de investigaci\u00f3n DeepSeek<\/a><\/li>\n
- \ud83d\udd17 Explorar el conjunto de datos BEIR<\/b> - Repositorio oficial BEIR<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
Capella AI Services est\u00e1 aqu\u00ed para ayudarle a crear aplicaciones impulsadas por IA con los mejores modelos de su clase. \u00a1Innovemos juntos!<\/b><\/p>","protected":false},"excerpt":{"rendered":"
Unlock advanced reasoning at a lower TCO for Enterprise AI Today, we\u2019re excited to share that DeepSeek-R1 is now integrated into Capella AI Services, available in preview! This powerful distilled model, based on Llama 8B, enhances your ability to build […]<\/p>","protected":false},"author":85541,"featured_media":16881,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[10092,10122,1815,2225,9973,9937],"tags":[10093,10087,9870],"ppma_author":[10050,8940],"class_list":["post-16866","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-services","category-artificial-intelligence-ai","category-best-practices-and-tutorials","category-cloud","category-generative-ai-genai","category-vector-search","tag-deepseek","tag-llama-models","tag-llms"],"acf":[],"yoast_head":"\n
DeepSeek Models Now Available in Capella AI Services<\/title>\n<meta name=\"description\" content=\"DeepSeek-R1 is now in Capella AI Services! Unlock advanced reasoning for enterprise AI at lower TCO. \ud83d\ude80 Sign up for early access!\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/deepseek-models-in-capella-ai-services\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"DeepSeek Models Now Available in Capella AI Services\" \/>\n<meta property=\"og:description\" content=\"DeepSeek-R1 is now in Capella AI Services! 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- \ud83d\ude80 Acceso anticipado a DeepSeek-R1<\/b> - Inscribirse en la lista de espera<\/a><\/li>\n
- \n