DEEPSEEK
NVIDIA Enhances PyTorch with NeMo Automodel for Efficient MoE Training
NVIDIA introduces NeMo Automodel to facilitate large-scale mixture-of-experts (MoE) model training in PyTorch, offering enhanced efficiency, accessibility, and scalability for developers.
Enhancing Biology Transformer Models with NVIDIA BioNeMo and PyTorch
NVIDIA's BioNeMo Recipes simplify large-scale biology model training with PyTorch, improving performance using Transformer Engine and other advanced techniques.
Enhancing AI Model Efficiency: Torch-TensorRT Speeds Up PyTorch Inference
Discover how Torch-TensorRT optimizes PyTorch models for NVIDIA GPUs, doubling inference speed for diffusion models with minimal code changes.
IBM Unveils Breakthroughs in PyTorch for Faster AI Model Training
IBM Research reveals advancements in PyTorch, including a high-throughput data loader and enhanced training throughput, aiming to revolutionize AI model training.
PyTorch Revolutionizes AI Accessibility for Developers
PyTorch, the deep-learning framework, is significantly enhancing AI accessibility for developers, backed by AMD's robust hardware support.
StreamingLLM Breakthrough: Handling Over 4 Million Tokens with 22.2x Inference Speedup
SwiftInfer, leveraging StreamingLLM's groundbreaking technology, significantly enhances large language model inference, enabling efficient handling of over 4 million tokens in multi-round conversations with a 22.2x speedup.