Simple and efficient training framework for long-context models
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Updated
Nov 2, 2025 - Python
Simple and efficient training framework for long-context models
A comprehensive framework for fine-tuning OpenAI models with streamlined data preparation, training, and evaluation workflows
A PyTorch framework that handles object detection across 6 different architectures (RetinaNet, Faster R-CNN, SSD, FCOS, and more). Takes care of the optimization setup and training quirks for each model.
Library for config based Neural Network Training
A comprehensive framework for developing YOLO family models, featuring streamlined workflows for training, validation, testing, and deployment through easy-to-use config files, enabling flexible customization to suit various object detection tasks.
A PyTorch framework for image classification covering 11 CNN architectures (ResNet, EfficientNet, MobileNet, etc.). Handles the optimization setup and training specifics for each model.
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