Welcome to Open LM Engine, a GitHub organization dedicated to developing high-performance tools, libraries, and methods for training large-scale machine learning models. Our mission is to push the boundaries of computational efficiency, enabling faster, more scalable, and cost-effective AI training.

Training large models—from transformer-based architectures to multimodal networks—demands innovative solutions across the stack: from custom CUDA kernels to memory-efficient training paradigms. At Open LM Engine, we:

• Develop optimized GPU kernels (other accelerators to follow) for deep learning workloads
• Explore sparsity, quantization, and other model compression techniques
• Build training frameworks for large scale models
• Share research-driven open-source tools with the community

We combine research insights with engineering best practices. Our work is inspired by:

• Recent breakthroughs in model efficiency (e.g., FlashAttention, ZeRO etc)
• Papers and implementations from top conferences (NeurIPS, ICML, ICLR)
• Real-world scalability needs in LLM and foundation model training

We welcome contributions from the community! Whether you're optimizing a kernel, fixing a bug, or proposing a new training strategy—every contribution counts.

📬 Open a PR or open an issue/discussion to get involved.

All repositories are open-source under Apache 2.0 license. See individual repos for details.