NodeShift

Google PaliGemma 2, the latest breakthrough in vision-language AI, is redefining what's possible in image and text processing. This state-of-the-art model combines the power of a Transformer decoder and Vision Transformer encoder to excel at tasks like image captioning, visual question answering, object detection, and segmentation. We’ve published a step-by-step guide to help you deploy this powerful model on a GPU-powered Virtual Machine using the NodeShift Cloud Platform. What you'll learn in the guide: ✅ Prerequisites and hardware requirements ✅ How to set up a NodeShift Cloud account ✅ Deploying a GPU-powered VM with 1x H100 SXM GPU ✅ Installing PaliGemma 2 and necessary libraries ✅ Testing and generating results using your own prompts Whether you're a researcher, developer, or tech enthusiast, this guide will help you unlock the full potential of PaliGemma 2. Read the full guide here: https://lnkd.in/gtUYgh3q #googleai #googlepaligemma2 #aimodels #cloud #gpus

As developers, we’re constantly building and deploying applications in complex environments. Thankfully, Docker simplifies this with the help of containerization. By packaging applications with their dependencies, Docker helps in maintaining consistency across different environments and makes collaboration easier. But how do you share your containerized app with others? Just like we share our code on GitHub, developers can share Docker images on Docker Hub, enabling others to pull the image and continue development seamlessly. 🔗 In our latest blog, we’ll cover: 1️⃣ How to create a Dockerfile for your app. 2️⃣ Building a Docker image. 3️⃣ Pushing it to Docker Hub for everyone to use. Dive into the blog here: https://lnkd.in/geqMnnHA #Docker #DevOps #DeveloperTools

Exciting news from AI at Meta The Llama 3.3 70B Instruct Model is here, and it’s nothing short of revolutionary. This multilingual language model supports multiple languages like English, German, French, Hindi, and Spanish, making it ideal for global dialogue and diverse text-based interactions. Key highlights of Llama 3.3: - 70 Billion Parameters for unparalleled performance. - 128k Context Length for handling extensive prompts and tasks. - Trained on 15 Trillion Tokens of diverse public datasets. - Optimized with supervised fine-tuning and reinforcement learning, ensuring alignment with human preferences for helpfulness and safety. With its state-of-the-art transformer architecture, Llama 3.3 is designed for high-quality text and code generation, taking multilingual AI capabilities to the next level. 🔥 At NodeShift, we’ve just published a Step-by-Step Guide on deploying Llama 3.3 on GPU-powered virtual machines. This guide walks you through 3 installation methods: 1️⃣ Ollama CLI - For quick terminal-based interaction. 2️⃣ Open WebUI - A user-friendly browser-based interface. 3️⃣ Hugging Face with Jupyter Notebooks - Ideal for researchers and developers looking for deep customization. 🔗 Read the guide here: https://lnkd.in/gVAWyTNi #Llama3 #Aimodels #MetaAI

If you are working on AI models, diving into machine learning, or exploring data science then you know how challenging it can be to manage packages, dependencies, and environments. That’s where Anaconda plays an important by simplifying these tasks to help you focus on building and innovating. If you're looking to install and setup Anaconda for your next project, we’ve got you covered! Our latest blog walks you through: 🔧 Installing Anaconda using the installer script 🔑 Setting up and initializing the “conda” environment ⚡ Tips to kickstart your projects seamlessly Whether you’re an experienced developer or just starting your journey into data science, this guide will help you set up the perfect foundation for your work. 🔗 Read the full guide here - https://lnkd.in/eYyAGayB #DataScience #Python #MachineLearning #AI

We’re thrilled to announce the launch of our latest step-by-step guide on deploying Nemotron-Mini-4B-Instruct using NodeShift’s powerful GPU Nodes! This compact yet robust model is designed for tasks like roleplaying, retrieval-augmented question answering, and function calling. Built with speed and efficiency in mind, it’s optimized for on-device use and supports up to 4,096 tokens of context. Leveraging advanced techniques like pruning, distillation, and quantization, this model delivers incredible performance with a smaller footprint. What You’ll Learn in the Guide: 1️⃣ System prerequisites and VM setup. 2️⃣ Creating a GPU Node on NodeShift. 3️⃣ Installing Ollama for model management. 4️⃣ Deploying and running Nemotron-Mini-4B-Instruct with step-by-step instructions. 5️⃣ Integrating with Open WebUI for an enhanced user experience. . 👉 Check out the full guide here: https://lnkd.in/gMN4e7N9 #Aimodels #nemotronmini #cloud

Blockchain is all about decentralization, and validator nodes are at the heart of it. These nodes play a critical role in: - Validating transactions - Securing the network - Ensuring smooth operations Whether it's participating in consensus or contributing to network decisions, validator nodes are essential for the health of blockchain ecosystems and maintaining decentralization. If you are curious about how they work or considering running your own to earn validator rewards, our latest blog is all you need. Here we will dive into: 💡 What validator nodes are and why they matter 💡 What you need to know before starting 💡 A step-by-step guide to running your own node Read the full guide here: https://lnkd.in/gpDwDdmb #Blockchain #ValidatorNode #Web3

The QwQ-32B-Preview-Abliterated model by huihui-ai is an innovative language model with 32 billion parameters, designed to excel in deep reasoning and analytical tasks. It takes the capabilities of the original QwQ-32B-Preview to the next level by reducing response restrictions and enabling more flexible, open-ended interactions. If you’re a developer or researcher looking to leverage the power of this model, we’ve got you covered! At NodeShift, we’ve published a step-by-step guide to help you deploy and interact with QwQ-32B-Preview-Abliterated on the cloud. Our guide simplifies the entire process, from setting up a GPU-powered Virtual Machine to running the model via Open WebUI or the terminal. Highlights of the Guide: - Comprehensive prerequisites for deploying the model. - How to set up a NodeShift GPU Node (VMs with GPUs like RTX A6000 for smooth execution). - Running the model on Open WebUI for an interactive experience. - Terminal-based deployment with Ollama for efficient access. 🔗 Check out the full guide here: https://lnkd.in/gq5cmx8B #qwq32b #aimodels

Grateful to have University of Oxford investment arm as part of the NodeShift team.

When working with Ubuntu Server, the terminal is a go-to, fast, and efficient tool, perfect for developers. But what if you need a more visual way to manage your server? Or maybe you're running applications that require a desktop interface? In our latest blog, we've put together a simple guide for setting up a Graphical User Interface (GUI) on Ubuntu Server. Here’s what's in for you: ✅ Step-by-step installation of the GUI environment ✅ Configuring the GUI environment on Ubuntu VM ✅ Connecting to the desktop through RDP (Remote Desktop Protocol) If you’re a beginner navigating Linux for the first time or just looking to make your server management workflow visually intuitive and user-friendly, this is for you. 👉 Checkout the full guide here: https://lnkd.in/gPJrZw8t #GUI #UbuntuServer

AI at Meta groundbreaking Llama 3.2 Vision model is here to redefine how we approach text and image tasks—whether it’s visual recognition, reasoning, or interactive image-based queries. If you’ve been waiting to dive into this advanced tech, our new step-by-step guide is your go-to resource! We’ve covered everything you need to deploy Llama 3.2 Vision in the cloud on a GPU-powered NodeShift Virtual Machine. From selecting the right setup to running the model using Open WebUI or Ollama, it’s all there. Curious about use cases? Whether it’s creating image captions, answering visual questions, or interpreting document layouts, this model has you covered. Ready to explore? Check out the guide here: https://lnkd.in/gr9T-MSp #llama3 #visionmodels #aimodels #llms #cloud #gpus