AI Blogs - Page 23#
Optimizing RoBERTa: Fine-Tuning with Mixed Precision on AMD
In this blog we explore how to fine-tune the Robustly Optimized BERT Pretraining Approach RoBERTa large language model, with emphasis on PyTorch's mixed precision capabilities. Specifically, we explore using AMD GPUs for mixed precision fine-tuning to achieve faster model training without any major impacts on accuracy.
Using statistical methods to reliably compare algorithm performance in large generative AI models with JAX Profiler on AMD GPUs
Using Statistical Methods to Reliably Compare Algorithm Performance in Large Generative AI Models with JAX Profiler on AMD GPUs
Accelerate PyTorch Models using torch.compile on AMD GPUs with ROCm
Accelerate PyTorch Models using torch.compile on AMD GPUs with ROCm
Accelerating models on ROCm using PyTorch TunableOp
Accelerating models on ROCm using PyTorch TunableOp
A Guide to Implementing and Training Generative Pre-trained Transformers (GPT) in JAX on AMD GPUs
A Guide to Implementing and Training Generative Pre-trained Transformers (GPT) in JAX on AMD GPUs
Deep Learning Recommendation Models on AMD GPUs
Deep Learning Recommendation Model on AMD GPU
Fine-tuning and Testing Cutting-Edge Speech Models using ROCm on AMD GPUs
This blog post demonstrates how to fine-tune and test three state-of-the-art machine learning Automatic Speech Recognition (ASR) models, running on AMD GPUs using ROCm.
TensorFlow Profiler in practice: Optimizing TensorFlow models on AMD GPUs
TensorFlow Profiler measures resource use and performance of models, helping identify bottlenecks for optimization. This blog demonstrates the use of the TensorFlow Profiler tool on AMD hardware.
SmoothQuant model inference on AMD Instinct MI300X using Composable Kernel
SmoothQuant model inference on AMD Instinct MI300X using Composable Kernel