PaddlePaddle provides a deep learning framework for training models across devices and platforms.
Open source
24 alternativesHow do MLX and Awesome Tensor Compilers compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | MLX | Awesome Tensor Compilers |
|---|---|---|
| What it is | MLX provides an array computing framework designed for Apple silicon devices. | List of awesome compiler projects and papers for tensor computation and deep learning. |
| Website | ||
| Type | Open-source project | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Not recorded | Not recorded |
| Open source | Yes | Not stated |
| Language | English | English |
| Alternatives |
Sites similar to both MLX and Awesome Tensor Compilers.
PaddlePaddle provides a deep learning framework for training models across devices and platforms.
QKeras provides quantization tools for deep learning with TensorFlow Keras.
The linfa project provides a machine learning framework written in Rust.
The MegEngine framework supports deep learning and automatic differentiation, according to its repository description.
FATE supports federated learning through an industrial grade framework.
Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.