Building a Low-Cost Local LLM Server to Run 70 Billion Parameter Models
A guest post from Fabrício Ceolin, DevOps Engineer at Comet. Inspired by the growing demand for large-scale language models, Fabrício…
How to Fine-Tune LLMs on Custom Datasets at Scale using Qwak and Comet
Welcome to Lesson 7 of 11 in our free course series, LLM Twin: Building Your Production-Ready AI Replica. You’ll learn…
4 Advanced RAG Algorithms to Optimize Retrieval
Welcome to Lesson 5 of 11 in our free course series, LLM Twin: Building Your Production-Ready AI Replica. You’ll learn…
Streaming Pipelines for Fine-tuning LLMs and RAG in Real-Time
In the 4th lesson, we will focus on the feature pipeline. The feature pipeline is the first pipeline presented in the 3 pipeline architecture: feature, training and inference…
Change Data Capture: Enabling Event-Driven Architectures
We have changes everywhere. Linkedin, Medium, Github, Substack can be updated everyday. To be able to have or Digital Twin…
Organize Your Prompt Engineering with CometLLM
Introduction Prompt Engineering is arguably the most critical aspect in harnessing the power of Large Language Models (LLMs) like ChatGPT. Whether…
Explainable AI: Visualizing Attention in Transformers
In this article we explore one of the most popular tools for visualizing the core distinguishing feature of transformer architectures:…
