Skip to main content
Back to top
Ctrl
+
K
Search
Ctrl
+
K
Search
Ctrl
+
K
Search
Ctrl
+
K
Get Started
Installation with Nvidia GPU
Installation with Ascend NPU (x86)
Installation with Ascend NPU (ARM)
Usage
Arguments API Reference
Basic Modules
Multimodal Data Processing
Usage of dyn_bsz
Support New Models — Guide and Checklist
Qwen3-VL MoE Integration Example
Qwen3-Omni-MoE Integration Example
Support New DiT Models — Guide and Reference
Checkpoint Conversion
Trainer
Agent Workflow Guide
HDFS FUSE Patch for DCP Consolidation
VeOmni Test Suite Overview
Hardware Support
Get Started with Ascend NPU
Typical Usage: Qwen3-VL 8B Training on Ascend NPU
Ascend Environment Variables
Precision Analysis and Troubleshooting Guide
Model Optimization - Profiling Collection, Analysis and Optimization Ideas
Ascend A2 Docker Image Build and Usage Guide
Ascend A3 Docker Image Build and Usage Guide
FAQ: Common Issues and Solutions for Ascend NPU
VeOmni on AMD ROCm
Examples
Qwen3 training guide
Qwen3.5 training guide
Qwen3 MoE training guide
Qwen3 VL training guide
Qwen3 Omni MoE training guide
Qwen3-Omni training with offline-extracted audio-enabled video
Wan2.1-I2V training guide
Wan2.1-T2V Training Guide
LTX-2.3 training guide
Qwen3 DPO training guide
Key Features
Adding a New Model to VeOmni
Custom Preprocessor Registry
EP+FSDP2 for Large-scale MoE Model Training
Extra Parallelism
Long-Sequence Training Using Ulysses
LoRA Fine-Tuning
Design
Kernel Selection in VeOmni
Fused MoE Kernel Notes
Local Parallel State Registry and Scoping
Modeling Code Generation (patchgen)
Unified Kernel Registry
verl Integration: Top-K Forward-KL Distillation via the VeOmni Engine
Transformers v5 Updates
Transformers v5 Notes
VeOmni Flash Attention Custom Name Adapter (Transformers 5.x)
VeOmni Fused Attention Interface
Transformers v5 MoE Weight Loading
Testing a New Model
System Settings
Light
Dark
Index
