Ultralytics YOLOv5 in PyTorch > ONNX > CoreML > TFLite
$ npx skills add ultralytics/yolov5Alternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
PyTorch implementation of the YOLO (You Only Look Once) v2
Ultralytics YOLOv5 in PyTorch > ONNX > CoreML > TFLite
$ npx skills add ultralytics/yolov5Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
$ npx skills add Lightning-AI/pytorch-lightningDeep Learning for humans
$ npx skills add keras-team/kerasUltralytics YOLO 🚀
$ npx skills add ultralytics/ultralyticsUltralytics YOLOv3 in PyTorch > ONNX > CoreML > TFLite
$ npx skills add ultralytics/yolov3🐍 Geometric Computer Vision Library for Spatial AI
$ npx skills add kornia/korniaDeep universal probabilistic programming with Python and PyTorch
$ npx skills add pyro-ppl/pyroRF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]
$ npx skills add roboflow/rf-detrAn Open Source Machine Learning Framework for Everyone
$ npx skills add tensorflow/tensorflowThe fastai deep learning library
$ npx skills add fastai/fastaiONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
$ npx skills add microsoft/onnxruntimeA toolkit for making real world machine learning and data analysis applications in C++
$ npx skills add davisking/dlibWe write your reusable computer vision tools. 💜
$ npx skills add roboflow/supervisionDeepfakes Software For All
$ npx skills add deepfakes/faceswap🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
$ npx skills add huggingface/datasetsTensors and Dynamic neural networks in Python with strong GPU acceleration
$ npx skills add pytorch/pytorchHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Yolo2 Pytorch if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.