TWEO: A Novel Transformer Architecture Improves Training Efficiency and Quantization
Published:Nov 28, 2025 14:33
•1 min read
•ArXiv
Analysis
This research paper introduces TWEO, a modified transformer architecture designed to simplify and accelerate training, particularly with low-precision formats. The focus on FP8 training and quantization suggests an effort to improve the efficiency and accessibility of large language models.
Key Takeaways
- •TWEO is a new transformer architecture.
- •The architecture focuses on FP8 training and quantization.
- •The goal is to improve training efficiency.
Reference
“TWEO enables FP8 training and quantization.”