2 Repos
Awesome GitHub RepositoriesMulti-Language Model Development
Frameworks that allow building and executing machine learning models using multiple different programming languages.
Distinguishing note: Other candidates focused on LLM development or general runtimes; this is specifically about ML model development in multiple languages.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Multi-Language Model Development. Refine with filters or upvote what's useful.
Awesome Multi-Language Model Development GitHub Repositories
Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
- dmlc/mxnet
dmlc/mxnet
20,812Auf GitHub ansehenMXNet is a deep learning framework and distributed machine learning engine designed for training and deploying neural networks. It functions as a hardware-agnostic backend that allows for the development of deep learning models through a hybrid of symbolic and imperative programming. The system distinguishes itself through automatic distributed parallelism, which scales training workloads across multiple GPUs and machines. It features an extensible hardware backend interface that enables the integration of custom accelerators and proprietary libraries without modifying the core source code.
Enables the building and execution of neural networks using various languages including Python, R, Scala, and Go.
C++ - iree-org/iree
iree-org/iree
3,819Auf GitHub ansehenIREE is an MLIR-based compiler toolchain and runtime designed to translate machine learning models from various frameworks into optimized binaries for execution across diverse hardware targets. It provides a unified pipeline to ingest models from PyTorch, TensorFlow, JAX, and ONNX, lowering them into a common intermediate representation for deployment on CPUs, GPUs, and bare-metal embedded systems. The project distinguishes itself through a bytecode virtual machine and a hardware abstraction layer that decouple high-level model logic from specific hardware instruction sets. It supports sophis
Supports building and executing machine learning models across different hardware targets using language-specific bindings.
C++compilercudajax
