Browsing: Guide

In this tutorial, we take a detailed, practical approach to exploring NVIDIA’s KVPress and understanding how it can make long-context language model inference more efficient. We…

to many areas of knowledge, helping us deal with uncertainty, calculate probabilities, and support decisions along the way. One of those areas that relies heavily on…

In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable information. We begin by installing the required dependencies…

every AI engineer knows well. You have just shipped a proof of concept. The demo went brilliantly. The LLM answered questions fluently, synthesised information on the…

print(“\n📊 MODEL EVALUATION\n”) eval_results = trainer.evaluate() print(” Evaluation Results:”) for key, value in eval_results.items(): if isinstance(value, float): print(f” {key:<25}: {value:.4f}”) from sklearn.metrics import classification_report, confusion_matrix preds_output…

In this tutorial, we implement an advanced, practical implementation of the NVIDIA Transformer Engine in Python, focusing on how mixed-precision acceleration can be explored in a…

In this tutorial, we build a complete end-to-end pipeline using NVIDIA Model Optimizer to train, prune, and fine-tune a deep learning model directly in Google Colab.…

In this tutorial, we take a deep dive into nanobot, the ultra-lightweight personal AI agent framework from HKUDS that packs full agent capabilities into roughly 4,000…

Quantum Mechanics is a fundamental theory in physics that explains phenomena at a microscopic scale (like atoms and subatomic particles). This “new” (1900) field differs from Classical Physics, which describes nature…

AI Officers tripled from the years 2019 to 2024, according to Linkedin Data. Now, roughly half of the largest companies in countries like the UK have…