Perplexity for LLM Evaluation
Perplexity is, historically speaking, one of the "standard" evaluation metrics for language models. And while recent years have seen a…
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…
The Role of Feature Stores in Fine-Tuning LLMs
Welcome to Lesson 6 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
Welcome to Lesson 4 of 11 in our free course series, LLM Twin: Building Your Production-Ready AI Replica. You’ll learn…
Change Data Capture: Enabling Event-Driven Architectures
Welcome to Lesson 3 of 11 in our free course series, LLM Twin: Building Your Production-Ready AI Replica. You’ll learn…
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…
