Neural networks training pipeline based on PyTorch
My repo for training neural nets using pytorch-lightning and hydra
YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).
Deep Learning training and deployment pipeline, reduce repetitive work from research to deployment
Machine Learning in Production
YoloLint is a tool for automatic validation of dataset structure, annotation files, and image sizes in YOLO projects. It helps you catch typical errors in directory structure, YAML files, annotation files, and now also ensures all your images have the correct size before you start model training.
SPIRA Model Trainer v2 (redesigned pipeline) by @danlawand
AI Message Labels: Packaging and pipelines for deep learning text classification models
Configurable PyTorch training pipeline
SPIRA Model Trainer v3 (productionized pipeline) by @lucasqml and @bolgheroni
A comprehensive framework for experimenting with and comparing modern object detection models including YOLO (v5, v8) and Detectron2. Features automated setup, training pipelines, benchmarking tools, and Jupyter notebooks for computer vision research and development.
🚀 Production-grade QLoRA fine-tuning for local GPUs - Comprehensive MLOps toolkit with intelligent setup wizard and production-ready training pipeline
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