Microsoft has released the OmniParser model on HuggingFace, a vision-based tool designed to parse UI screenshots into structured elements, enhancing intelligent GUI automation across platforms without relying on additional contextual data.
Simon Willison explains how to use the mistral.rs library in Rust to run the Llama Vision model on a Mac M2 laptop. He provides a detailed example and discusses the memory usage and GPU utilization.
Meta releases Llama 3.2, which features small and medium-sized vision LLMs (11B and 90B) alongside lightweight text-only models (1B and 3B). It also introduces the Llama Stack Distribution.
MLX-VLM: A package for running Vision LLMs on Mac using MLX.
This article explores how to incorporate images into a RAG (Retrieval-Augmented Generation) knowledgebase using Large Language Models (LLMs) with vision capabilities. It provides a step-by-step guide to collecting, uploading, and transcribing images for a richer and more detailed knowledgebase.
A website for the Seeed Watcher, a physical AI agent for space management, with features like product catalog, ecosystem, support, and company information.
This article provides a step-by-step guide on fine-tuning the Florence-2 model for object detection tasks, including loading the pre-trained model, fine-tuning with a custom dataset, and evaluating the model's performance.
In this article, the author tests ChatGPT-4o's vision feature by providing it with a series of images and asking it to describe what it can see. The author is impressed with the model's accuracy and descriptive abilities.
