3 repos
Awesome GitHub RepositoriesTraining Orchestration Systems
Platforms and utilities that manage the end-to-end lifecycle, execution, and monitoring of training jobs, distinct from specific algorithms by focusing on workflow management.
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Training Orchestration Systems. Refine with filters or upvote what's useful.
Awesome Training Orchestration Systems GitHub Repositories
We'll search the best matching repositories with AI.
- keras-team/keras
Keras is a high-level deep learning framework designed for constructing and training neural networks through the composition of modular, functional layers. It serves as a comprehensive modeling toolkit that provides standardized procedures for defining, evaluating, and deploying complex architectures. By utilizing a di
Pythondata-sciencedeep-learningjax - deepfakes/faceswap
Faceswap is a comprehensive framework for automated media manipulation and neural face synthesis. It provides a modular pipeline that manages the entire lifecycle of facial feature extraction, deep learning model training, and image conversion. By coordinating complex computer vision workflows, the system enables users
Pythondeep-face-swapdeep-learningdeep-neural-networks - unslothai/unsloth
Unsloth is a high-performance training and inference platform designed to optimize the lifecycle of large language and multimodal models. It provides a comprehensive engine for fine-tuning, executing, and managing models locally, with a focus on reducing memory consumption and increasing compute speed on consumer-grade
Pythonagentdeepseekdeepseek-r1
Explore sub-tags
- Training Lifecycle Management1 sub-tagSystems for managing the end-to-end training process, including the implementation of custom loss functions and unique training objectives.
- Training Loop ManagersFrameworks that automate the execution of model training loops, including batch processing and periodic model saving.
- Training Methodologies1 sub-tagStructured approaches and techniques for model training, including the integration of reinforcement learning methods.