A high-throughput and memory-efficient inference and serving engine for LLMs
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Updated
Jun 1, 2024 - Python
PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab.
A high-throughput and memory-efficient inference and serving engine for LLMs
Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project
Visualizer for neural network, deep learning and machine learning models
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Online Handwritten Text Recognition (HTR) system implemented with PyTorch. Based on https://doi.org/10.1007/s10032-020-00350-4.
Collection of bet practices, reference architectures, examples, and utilities for foundation model development and deployment on AWS.
Quick and easy Diffusers CLI
A principled library for tuning, training and evaluating tabular data synthesis on fidelity, privacy and utility.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
DyNA is a framework for dynamic, data-driven nonlinear signal propagation, inspired by biological neural networks.
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
Convolutional Neural Network inference library running on CUDA
Collaborative and hybrid recommendation systems
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
Determining chess game state from an image.
VITS-based Voice Conversion focused on simplicity, quality and performance.
Accelerate your training with this open-source library. Optimize performance with streamlined training and serving options with JAX. 🚀
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Created by Facebook's AI Research lab (FAIR)
Released September 2016
Latest release about 2 months ago