Brand new TTS solution

Fast and memory-efficient exact attention

tiktoken is a fast BPE tokeniser for use with OpenAI's models.

An Easy-to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral)

A native PyTorch Library for large model training

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Related code and datasets on NetBench: A Large-Scale and Comprehensive Network Traffic Benchmark Dataset for Foundation Models

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

The official Meta Llama 3 GitHub site

🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

Openreviewers: Multi Agent Academic Review Simulation System

Fast & Simple repository for pre-training and fine-tuning T5-style models

Instruct-tune LLaMA on consumer hardware

Officially Accepted to IEEE Transactions on Medical Imaging (TMI, IF: 11.037) - Special Issue on Geometric Deep Learning in Medical Imaging.

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

Strategies for Pre-training Graph Neural Networks

[AAAI'22] HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images

FaceChain is a deep-learning toolchain for generating your Digital-Twin.

开源社区第一个能下载、能运行的中文 LLaMA2 模型！

Open-source KVM software

Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans

Convert NIfTI volume to triangulated mesh using marching cubes

Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

Automated Extraction and Classification of Pulmonary Lung Nodules from CT Scans

Code for preprocessing the LIDC-IDRI lung cancer screening CT scan dataset

This is the preprocessing step of the LIDC-IDRI dataset