A PyTorch native library for training speculative decoding models

A framework for efficient model inference with omni-modality models

Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.

Cross-platform transformer training

VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo

Discrete Diffusion Forcing (D2F): dLLMs Can Do Faster-Than-AR Inference

Train speculative decoding models effortlessly and port them smoothly to SGLang serving.

A Datacenter Scale Distributed Inference Serving Framework

EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL

FlashMLA: Efficient Multi-head Latent Attention Kernels

how to optimize some algorithm in cuda.

Entropy Based Sampling and Parallel CoT Decoding

documentation for content creation

Pytorch implementation of Transfusion, "Predict the Next Token and Diffuse Images with One Multi-Modal Model", from MetaAI

CUDA Templates and Python DSLs for High-Performance Linear Algebra

A fast multimodal LLM for real-time voice

A high-throughput and memory-efficient inference and serving engine for LLMs

Manages vllm-nccl dependency

CUDA/Metal accelerated language model inference