Kubeflow is a Kubernetes machine learning platform and containerized toolkit designed to orchestrate the entire machine learning lifecycle. It functions as an MLOps workflow orchestrator and infrastructure layer for building, training, and deploying models within containerized environments. The project provides specialized infrastructure for scaling compute resources and managing GPU workloads for large-scale distributed training. It automates the transition of models from experimental development to production through workflow orchestration and model deployment services. The platform covers
Hyperparameter Experiments with TensorFlow and Keras
Axolotl is a configuration-driven framework designed for the fine-tuning, evaluation, and quantization of large language models. It functions as a comprehensive orchestrator for distributed training, enabling users to manage complex workflows across multi-node and multi-GPU environments. By utilizing structured configuration files, the platform streamlines the setup of training parameters, dataset paths, and hardware distribution strategies. The project distinguishes itself through its support for diverse training methodologies, including full-parameter tuning, parameter-efficient adaptation,
Corenet is a deep learning training framework and computer vision model library designed for developing neural networks across vision, text, and audio modalities. It functions as a distributed training orchestrator for scaling workloads across multiple compute nodes and provides a multimodal data pipeline for processing image, text, and video data. The project includes a model conversion toolkit for transforming weights and architectures between different machine learning frameworks. It also provides tools for optimizing model performance on Apple Silicon and reducing response latency in gene
TFX is an end-to-end platform for deploying production ML pipelines
Las características principales de tensorflow/tfx son: MLOps and Infrastructure, Training and Orchestration.
Las alternativas de código abierto para tensorflow/tfx incluyen: kubeflow/kubeflow — Kubeflow is a Kubernetes machine learning platform and containerized toolkit designed to orchestrate the entire… autonomio/talos — Hyperparameter Experiments with TensorFlow and Keras. axolotl-ai-cloud/axolotl — Axolotl is a configuration-driven framework designed for the fine-tuning, evaluation, and quantization of large… bentoml/bentoml — BentoML is a machine learning model serving framework and GPU-accelerated inference server designed to package,… bindsnet/bindsnet. apple/corenet — Corenet is a deep learning training framework and computer vision model library designed for developing neural…