4M vs. YOLOv4 Tiny: Compared and Contrasted

Models

The 4M model is a versatile multimodal Transformer model developed by EPFL and Apple, capable of handling a handful of vision and language tasks.

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset

Model Type

Multimodal Model

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

ResNet-D, YOLO

Frameworks

PyTorch

Darknet

Annotation Format

Instance Segmentation

GitHub

GitHub Stars

1.1k

License

Apache 2.0

YOLO

Paper

Training Notebook

Deploy Model

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.