Models
YOLOv4 Tiny vs. YOLOS

YOLOv4 Tiny vs. YOLOS

Both YOLOv4 Tiny and YOLOS are commonly used in computer vision projects. Below, we compare and contrast YOLOv4 Tiny and YOLOS.

Models

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YOLOv4 Tiny

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

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.
Learn more about YOLOS
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
ResNet-D, YOLO
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Transformer, YOLO
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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Darknet
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PyTorch
GitHub
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View Repo
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View Repo
GitHub Stars
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812+
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License
YOLO
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MIT
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
Compare Alternatives
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Compare YOLOv4 Tiny and YOLOS with Autodistill

Compare YOLOv4 Tiny vs. YOLOS

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.