Supervised Fine-tuning: customizing LLMs

In the rapidly evolving field of Natural Language Processing (NLP), fine-tuning has…

Finetuning an LLM: RLHF and alternatives (Part I)

Introduction

Why we’re switching to Hugging Face Inference Endpoints, and maybe you should too

Hugging Face recently launched Inference Endpoints. In this blog post we look at some of the pros and cons, and why we’re…

Prompt Engineering — Part II — How to construct prompts

Text embedding models: how to choose the right one

Automatic Prompt Engineering (Part I: Main Concepts)

Prompt Engineering — Part III — Examples of prompt construction

Eight examples is all you need ✨

It is no secret that the power of machine learning models comes from the data that they are trained…

Automatic Prompt Engineering (Part IV: Hands-on: Evaluation)

Automatic Prompt Engineering (Part II: Building an APE Workflow)