Build Real-Time AI Agents with Gradient and Serverless Functions
Easily create valuable AI-powered agents that can retrieve and process real-time information using the cloud provider’s Gradient Platform.
PyTorch 101, Understanding Graphs, Automatic Differentiation and Autograd
In this article, we dive into how PyTorch’s Autograd engine performs automatic differentiation.
Scale a Video-on-Demand Platform Using cloud servers
Learn how to build a video-on-demand platform on the cloud provider. Compare performance metrics between basic and premium droplets for optimal scaling.
Image Processing Part 5: Arithmetic, Bitwise, and Masking
In this 5th part of the image processing series, we discuss more on the Arithmetic and bitwise operations, and masking of images in Python. It is recommended that the [previous articles](/community/tutorials/image-transformation-with-python-opencv) be run through, before starting off on your masked learning adventure here. Setting up the environment The following lines of code are used in […]
Deploy LLMs Like Phi-3 on the cloud provider Using Ollama + WebUI
Learn how to deploy the Phi-3 language model on a cloud servers using Ollama and Open WebUI. Learn to set up your local LLM chatbot.
Running DeepScaleR-1.5B with vLLM on the cloud provider
‘The purpose of this tutorial is two-fold: to give readers an overview of DeepScaleR-1.5B-Preview, an open-source reasoning model, as well as demonstrate how they can run this model on the cloud provider’s GPU Droplets.’
An Introduction to Machine Learning
Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Although machine learning is a field within computer…
Run LLMs with Ollama on H100 GPUs for Maximum Efficiency
This step-by-step tutorial teaches how to run large language model with Ollama on H100 GPUs. Ollama contains a library of LLMs and users can run with ease and privacy.
A Comprehensive Guide to YOLO NAS: Object Detection with Neural Architecture Search
In this article, we explore the architecture of YOLO NAS. We will understand its neural network design, optimization techniques, and highlight the specific improvements it brings over traditional YOLO models.
Understanding t-SNE: Dimensionality Reduction Technique
Learn how t-SNE simplifies dimensionality reduction and data visualization by preserving data structures. Explore parameters and Python implementation.