Models
4M vs. EfficientNet

4M vs. EfficientNet

Both 4M and EfficientNet are commonly used in computer vision projects. Below, we compare and contrast 4M and EfficientNet.

Models

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4M

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

EfficientNet is from a family of image classification models from GoogleAI that train comparatively quickly on small amounts of data, making the most of limited datasets.
Learn more about EfficientNet
Model Type
Multimodal Model
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Classification
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Model Features
Item 1 Info
Item 2 Info
Architecture
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CNN
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Frameworks
PyTorch
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Keras
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
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View Repo
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View Repo
GitHub Stars
1.1k
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License
Apache 2.0
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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
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Compare 4M and EfficientNet with Autodistill

Compare 4M vs. EfficientNet

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.