Guides

How to evaluate object detection models with Labelbox Model Foundry

Explore how Model Foundry enables teams to efficiently compare and select the right foundation model to kickstart computer vision development, decreasing costs and accelerating time-to-value.

Zero-Shot Learning vs. Few-Shot Learning vs. Fine-Tuning: A technical walkthrough using OpenAI's APIs & models

With large language models (LLMs) gaining popularity, new techniques have emerged for applying them to NLP tasks. Three techniques in particular — zero-shot learning, few-shot learning, and fine-tuning — take different approaches to leveraging LLMs. In this guide, we’ll walk through the key difference between these techniques and how to implement them.  We’ll walk through a case study of extracting airline names from tweets to compare the techniques. Using an entity extraction dataset, we’ll be

How to use the model Foundry for automated data labeling and enrichment

Learn how to harness the power of Model Foundry to automate and enrich data workflows in Labelbox.

How to boost retail profitability with AI-powered shelf object detection

Learn how to leverage Labelbox’s data-centric AI platform to build a robust shelf object detection model to boost retail profitability.

How to fine-tune OpenAI’s GPT-3.5 Turbo using Labelbox

In this guide, we’ll cover how to leverage Open AI’s GPT-3.5 and Labelbox to simplify the fine-tuning process, allowing you to rapidly iterate and refine your models’ performance on specific data.

How to fine-tune Vertex AI LLMs with Labelbox

In this guide, we’ll cover how to leverage Vertex AI and Labelbox to simplify the fine-tuning process, allowing you to rapidly iterate and refine your models’ performance on specific data.

How to build a powerful product recommendation system for retail

Learn how to leverage Labelbox's data-centric AI platform to build a robust AI-powered product recommendation system to power personalized experiences for retail.

A guide to the Data I/O process in Labelbox

In this guide, we take an in-depth look at the Data I/O process and offer a step-by-step guide to streamline your interaction with the Labelbox platform.

How to uncover model errors with Labelbox Model

Explore how to perform model error analysis using Labelbox, with a specific focus on utilizing the Gallery View and Model Metrics.

Using Meta's Segment Anything (SAM) model on video with Labelbox's model-assisted labeling

Learn how to use Meta’s Segment Anything (SAM) model with YOLOv8 to automatically detect, classify, and draw masks on video.