Transformer Neural Networks

FineTuning Gemma 3n for Medical VQA on ROCOv2

What if a radiologist facing a complex scan in the middle of the night could ask an AI assistant for a second opinion, right from their local workstation? This isn't

Computer Vision, Generative AI, Generative Models, LLMs, Multimodal Models, NLP, Transformer Neural Networks, Vision Language Models, Vision Transformer, VLMs

FramePack: Video Diffusion, but feels like Image Diffusion

Ever watched an AI-generated video and wondered how it was made? Or perhaps dreamed of creating your own dynamic scenes, only to be overwhelmed by the complexity or the need

AI Art Generation, AI Research Papers, Artificial Intelligence, Computer Vision, Deep Learning, Diffusion Models, Generative AI, Generative Models, GPUs, GUI, Neural Network, PyTorch, Transformer Neural Networks, video diffusion, Vision Transformer

RF-DETR by Roboflow: Speed Meets Accuracy in Object Detection

Object detection has come a long way, especially with the rise of transformer-based models. RF-DETR, developed by Roboflow, is one such model that offers both speed and accuracy. Using Roboflow’s

Computer Vision, Object Detection, Transformer Neural Networks

Introduction to GPT-4o Image Generation – Here’s What You Need to Know

GPT-4o image generation is a game-changer! With native support in ChatGPT, you can now create stunning visuals from text prompts, refine them, and explore styles like Studio Ghibli or photorealism.

AI Art Generation, Computer Vision, Deep Learning, Diffusion Models, Generative AI, Generative Models, Transformer Neural Networks

WhisperX Automatic Speech Recognition (ASR) with Nemo Speaker Diarization : Speech-to-Text

This article presents ASR with Diarization using OpenAI Whisper and Nvidia Nemo Toolkit.

Artificial Intelligence, Deep Learning, Speech Recognition, Transformer Neural Networks

Building MobileViT Image Classification Model from Scratch In Keras 3

In the rapidly evolving field of deep learning, the challenge often lies not just in designing powerful models but also in making them accessible and efficient for practical use, especially

AI Research Papers, CNN, Computer Vision, Convolution, Deep Learning, Keras, Transformer Neural Networks, Vision Transformer