AI - Applications & Models - Page 7#
Benchmarking Reasoning Models: From Tokens to Answers
Learn how to benchmark reasoning tasks. Use Qwen3 and vLLM to test true reasoning performance, not just how fast words are generated.
Instella-T2I: Open-Source Text-to-Image with 1D Tokenizer and 32× Token Reduction on AMD GPUs
Explore Instella-T2I: AMD’s open-source text-to-image model, built on MI300X GPUs with novel tokenizer and LLM-based encoder for scalable image generation.
Fine-tuning Robotics Vision Language Action Models with AMD ROCm and LeRobot
Speed up robotics AI with AMD ROCm and LeRobot: fine-tune VLAs on Instinct GPUs and deploy on Ryzen AI. Follow the tutorial to get started.
Accelerating Video Generation on ROCm with Unified Sequence Parallelism: A Practical Guide
A practical guide for accelerating video generation with HunyuanVideo and Wan 2.1 using Unified Sequence Parallelism on AMD GPUs.
Nitro-T: Training a Text-to-Image Diffusion Model from Scratch in 1 Day
Nitro-T is a family of text-to-image diffusion models developed by AMD to demonstrate efficient large-scale training on Instinct™ MI300X GPUs. Trained from scratch in under 24 hours
Enabling Real-Time Context for LLMs: Model Context Protocol (MCP) on AMD GPUs
Learn how to leverage Model Context Protocol (MCP) servers to provide real time context information to LLMs through a chatbot example on AMD GPUs
Continued Pretraining: A Practical Playbook for Language-Specific LLM Adaptation
A step by step guide to adapting LLMs to new languages via continued pretraining, with Poro 2 boosting Finnish performance using Llama 3.1 and AMD GPUs
Aligning Mixtral 8x7B with TRL on AMD GPUs
This blog demonstrates how to fine-tune and align Mixtral 8x7B with TRL using DPO and evaluate it on AMD GPUs.
Introducing Instella-Long: A Fully Open Language Model with Long-Context Capability
Learn about Instella-Long: AMD’s open 3B language model supporting 128K context, trained on MI300X GPUs, outperforming peers on long-context benchmarks.
LLM Quantization with Quark on AMD GPUs: Accuracy and Performance Evaluation
Learn how to use Quark to apply FP8 quantization to LLMs on AMD GPUs, and evaluate accuracy and performance using vLLM and SGLang on AMD MI300X GPUs.
Reproduce AMD's MLPerf Training v5.0 Submission Result with Instinct™ GPUs
Follow this step-by-step guide to reproduce AMDs MLPerf 5.0 Training Submission with Instinct GPUs using ROCm
AMD’s MLPerf Training Debut: Optimizing LLM Fine-Tuning with Instinct™ GPUs
Explore the techniques we used to improve the training performance on MI300X and MI325X in our MLPerf Training 5.0 submission.