React Native app for running LLMs, vision models, and Stable Diffusion on-device on iOS and Android without internet access. opensource.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A general statistics and machine learning library.
An open-source cross-platform performance library for deep learning applications.
OneFlow is a performance-centered and open-source deep learning framework.
Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support.
An ONNX (Open Neural Network eXchange) API and backend for typeful, functional deep learning in Scala (3).
A library that enables training PyTorch models with differential privacy.
A list of open LLMs available for commercial use.
Grok - An LLM by xAI with and open weights. opensource.
Source code and experiments results for TGS Salt Identification Challenge.
Source code and experiments results for Airbus Ship Detection Challenge.
Source code for Toxic Comment Classification Challenge.
Source code and experiments results for Santander Value Prediction Challenge.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
OpenAI's point cloud diffusion for 3D model synthesis.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.
A PyTorch-based framework to train and validate the models producing high-quality embeddings.