HLearning's starred repositories
stable-diffusion-webui
Stable Diffusion web UI
googletest
GoogleTest - Google Testing and Mocking Framework
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
LLaMA-Factory
Unify Efficient Fine-Tuning of 100+ LLMs
diffusionbee-stable-diffusion-ui
Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
Open-Sora-Plan
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
seamless_communication
Foundational Models for State-of-the-Art Speech and Text Translation
Fay
Fay is an open-source digital human framework integrating language models and digital characters. It offers retail, assistant, and agent versions for diverse applications like virtual shopping guides, broadcasters, assistants, waiters, teachers, and voice or text-based mobile assistants.
TensorRT-LLM
TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
streaming-llm
[ICLR 2024] Efficient Streaming Language Models with Attention Sinks
video-retalking
[SIGGRAPH Asia 2022] VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
mlx-examples
Examples in the MLX framework
chat-with-mlx
Chat with your data natively on Apple Silicon using MLX Framework.
riscv-tools
RISC-V Tools (ISA Simulator and Tests)
pyhpc-benchmarks
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket: