Models
Phi-3.5 vs. YOLOv3 PyTorch

Phi-3.5 vs. YOLOv3 PyTorch

Both Phi-3.5 and YOLOv3 PyTorch are commonly used in computer vision projects. Below, we compare and contrast Phi-3.5 and YOLOv3 PyTorch.

Models

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Phi-3.5

Learn more about Phi-3.5
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YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
Learn more about YOLOv3 PyTorch
Model Type
Multimodal Model
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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YOLO
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Frameworks
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PyTorch
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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
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7.2k+
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License
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GPL-3.0
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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 Phi-3.5 and YOLOv3 PyTorch with Autodistill

Compare Phi-3.5 vs. YOLOv3 PyTorch

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.