Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
-
Updated
Jun 1, 2024 - Rust
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.
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. 🚀
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
A high-throughput and memory-efficient inference and serving engine for LLMs
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.
Image Debanding using Inversion by Direct Iteration
Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks
The repository is for Skoltech Master's thesis work on "GAN-based Multi-Image Super-Resolution for Remote Sensing Imagery"
Serve, optimize and scale PyTorch models in production
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
A PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
Low-code framework for building custom LLMs, neural networks, and other AI models
Open standard for machine learning interoperability
a collection of small machine learning projects
Everything is PyTorch. A Journey into every aspect of PyTorch.
Created by Facebook's AI Research lab (FAIR)
Released September 2016
Latest release about 2 months ago