UbiOps
¿Qué es UbiOps?
UbiOps es una plataforma de infraestructura de IA que ayuda a los equipos a ejecutar rápidamente sus cargas de trabajo de IA y ML como microservicios confiables y seguros, sin alterar los flujos de trabajo existentes. Permite una integración perfecta en los bancos de trabajo de ciencia de datos, eliminando la carga de gestionar una infraestructura en la nube costosa.
¿Cómo usar UbiOps?
Lanza fácilmente productos de IA escalables con UbiOps. Intégralo en tu banco de trabajo de ciencia de datos en minutos y evita la configuración y gestión de infraestructura en la nube que consume mucho tiempo.
Características principales de UbiOps
Implementación rápida de cargas de trabajo de IA/ML a nivel de producción
Servicio y orquestación escalable de modelos de IA
Capacidades integradas para productos de IA avanzados
Casos de uso de UbiOps
Desarrollo de productos de IA para startups u organizaciones grandes
Ofrecer servicios de IA o ML confiables sin preocupaciones de infraestructura
FAQ de UbiOps
¿Qué se puede implementar con UbiOps?
¿Qué tan seguro es UbiOps para datos sensibles?
UbiOps Correo electrónico de soporte, contacto de servicio al cliente, contacto de reembolso, etc.
Más contacto, visite la página de contacto(https://ubiops.com/contact-us/)
UbiOps empresa
UbiOps Nombre de la empresa: Dutch Analytics B.V. .
UbiOps Dirección de la empresa: LAB42, room L2.16, Science Park 900, 1098 XH Amsterdam, the Netherlands The Hague office Wilhelmina van Pruisenweg 35 2595 AN, The Hague The Netherlands +31 70 792 00 91 New York office 228 E. 45th St., Suite 9E New York, NY 10017.
Más información sobre UbiOps, visite la página acerca de nosotros(https://ubiops.com/about-us/) .
UbiOps Iniciar sesión
UbiOps Enlace de inicio de sesión: https://app.ubiops.com/sign-in
UbiOps Registrarse
UbiOps Enlace de registro: https://app.ubiops.com/sign-up/
Youtube de UbiOps
Enlace de Youtube de UbiOps: https://youtube.com/channel/UCQBpeuKmGcRWptc2Ldumyrw
Linkedin de UbiOps
Enlace de Linkedin de UbiOps: https://linkedin.com/company/ubiops
Twitter de UbiOps
Enlace de Twitter de UbiOps: https://twitter.com/UbiOps_
Github de UbiOps
Enlace de Github de UbiOps: https://github.com/UbiOps
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Deploy Llama 3 in 5 minutes (tutorial)
Hey there, data scientists! 🌟 In today’s tutorial, we’re deploying Meta’s latest large language model, Llama 3, on UbiOps in under 15 minutes. Llama 3 is the newest addition to Meta's Llama series, offering impressive capabilities with its 8 billion parameter version. Whether you're looking to harness its power for advanced tasks or just exploring its potential, this tutorial will help get you started. In this step-by-step guide, we'll walk you through every detail, ensuring you can deploy the Llama 3 8B instruct model effortlessly. Plus, discover tips on building a user-friendly front-end for your chatbot using Streamlit! You can also follow the detailed, written version of this tutorial here: https://ubiops.com/deploy-llama3-with-ubiops/ 🔍 Learn how to: Set up a UbiOps account with GPU access Create a custom environment for your model Set up and configure your deployment Make inference requests to test your deployed model ⚙️ To successfully complete this guide, you will need: UbiOps account with GPU access Supporting files and code snippets included in the full tutorial: https://ubiops.com/deploy-llama3-with-ubiops/ 🚀 UbiOps: - Free trial account sign-up: https://app.ubiops.com/sign-up/ - Slack community: https://join.slack.com/t/ubiops-community/shared_invite/zt-np02blts-5xyFK0azBOuhJzdRSYwM_w - Contact form: http://ubiops.com/contact-us/ - Blog page for more guides: https://ubiops.com/blog/ - Documentation: https://ubiops.com/docs/ 🎥 Don't miss out on this opportunity to level up your AI and machine learning game. Hit that like button, share with your fellow tech enthusiasts, and subscribe to stay updated on our latest tutorials and insights. Happy coding! 🚀 Chapters: 0:00 Introduction 0:20 What's Llama 3? 0:55 Create UbiOps account 1:12 Create environment 1:26 Create deployment 1:53 Create version 2:12 Hugging Face token 2:43 Make inference request 3:07 Streamlit front-end 3:36 Conclusion #AI #MachineLearning #Llama3 #UbiOps #Tutorial #Tech #DataScience #Chatbot #Deployment
Fine-tune Mistral 7b on your own documents in under 5 minutes
Welcome back, data enthusiasts! 🌟 In today's tutorial, we're diving deep into the realm of fine-tuning to craft a domain-expert AI assistant. In this tutorial, we'll guide you through each step, from setting up your accounts and environments to preprocessing your data and executing the fine-tuning process. Whether you're a seasoned data scientist or just starting out, this hands-on guide will equip you with the skills to create a customized chatbot tailored to your unique use case. Join us as we explore the intricacies of Parameter-Efficient Fine-Tuning (PEFT) with Low Rank Adaptation (LoRA) to retrain an open-source Large Language Model (LLM) on UbiOps documentation. This is a faster, cheaper, and less resource-intensive fine-tuning method. You can also follow the detailed, written version of this tutorial here: https://ubiops.com/fine-tune-a-model-on-your-own-documentation/ 🔍 Learn how to: - Create a UbiOps and HuggingFace account to gain access to the Mistral-7b-instruct-v0.2 model. - Prepare documents to be used as training data. - Initiate a training run to fine-tune the model. ⚙️ To successfully complete this guide, you will need: - UbiOps account with training functionality enabled (see below) - Supporting files and code snippets included in the full tutorial: https://ubiops.com/implementing-rag-for-your-llm-mistral/ 🚀 UbiOps: - Free trial account sign-up: https://app.ubiops.com/sign-up/ - Slack community: https://join.slack.com/t/ubiops-community/shared_invite/zt-np02blts-5xyFK0azBOuhJzdRSYwM_w - Contact form: http://ubiops.com/contact-us/ - Blog page for more guides: https://ubiops.com/blog/ - Documentation: https://ubiops.com/docs/ 🎥 Don't miss out on this opportunity to level up your AI and machine learning game. Hit that like button, share with your fellow tech enthusiasts, and subscribe to stay updated on our latest tutorials and insights. Happy coding! 🚀 Chapters: 0:00 Introduction 1:39 Create accounts 1:52 Prepare training data 2:40 Fine-tune the model 3:17 Test the model 3:54 Conclusion #AI #MachineLearning #finetuning #mistral #LLM #Tutorial #Tech #DataScience #UbiOps
Deploy LLaMA 2 with a Streamlit front-end in under 15 minutes (including CPU vs GPU benchmark)
In this guide, we explain how to deploy LLaMA 2, an open-source Large Language Model (LLM), using UbiOps for easy model hosting and Streamlit for creating a chatbot UI. The guide provides step-by-step instructions for packaging a deployment, loading it into UbiOps, configuring compute on GPUs and CPUs, generating API tokens, and integrating with Streamlit for the front-end. We conclude with a benchmark test showing that GPUs can provide over 30x faster processing speeds than CPUs. This guide aims to make cutting-edge AI accessible by allowing anyone to deploy their own LLaMA 2 chatbot in minutes. To successfully complete this guide, you will need: - Python 3.9 or higher installed - Streamlit library installed - UbiOps Client Library installed (see below) - UbiOps account (see below) Here are some useful links to support you: ⚒️ Materials: - Written “Deploy LlaMA 2” guide: https://ubiops.com/deploy-llama-2-with-a-customizable-front-end-in-under-15-minutes-using-only-ubiops-python-and-streamlit/#unique-identifier - HuggingFace LLaMA 2-7b model authorization: https://huggingface.co/meta-llama/Llama-2-7b-hf - UbiOps documentation on deployment package structure: https://ubiops.com/docs/deployments/deployment-package/deployment-structure/ - Streamlit + LLaMA tutorial: https://blog.streamlit.io/how-to-build-a-llama-2-chatbot/ - UbiOps + Streamlit integration tutorial: https://ubiops.com/docs/ubiops_tutorials/streamlit-tutorial/streamlit-tutorial/ - More info on LlaMA 2: https://ai.meta.com/llama/ 🚀 UbiOps: - Free account sign-up: https://app.ubiops.com/sign-up/ - Slack community: https://join.slack.com/t/ubiops-community/shared_invite/zt-np02blts-5xyFK0azBOuhJzdRSYwM_w - Contact form: http://ubiops.com/contact-us/ - Blog page for more guides: https://ubiops.com/blog/ Chapters: 0:00 - Overview 0:57 - Getting started 1:55 - Build deployment package 4:19 - Load & configure deployment 6:02 - Build front-end 7:40 - Prompt your model 8:51 - CPU vs GPU benchmark 10:44 - Final thoughts #chatgpt #promptengineering #chatbot #llama #artificialintelligence #python #huggingface -------------------- More useful UbiOps content below: Website: https://ubiops.com/ Blog: https://ubiops.com/blog/ Documentation: https://ubiops.com/docs/ Instant models: https://ubiops.com/community-models-ubiops/
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