Applications & models - Page 8#
Explore the latest blogs about applications and models in the ROCm ecosystem, including machine learning frameworks, AI models, and application case studies.
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.
High-Throughput BERT-L Pre-Training on AMD Instinct™ GPUs: A Practical Guide
Learn how to optimize BERT-L training with mixed precision and Flash Attention v2 on AMD Instinct GPUs — follow our tested MLPerf-compliant step-by-step guide.
Scale LLM Inference with Multi-Node Infrastructure
Learn how to horizontally scale LLM inference using open-source tools on MI300X, with vLLM, nginx, Prometheus, and Grafana.
AMD Integrates llm-d on AMD Instinct MI300X Cluster For Distributed LLM Serving
AMD Integrates llm-d on AMD Instinct MI300X Cluster For Distributed LLM Serving
Accelerate DeepSeek-R1 Inference: Integrate AITER into SGLang
Boost DeepSeek-R1 with AITER: Step-by-step SGLang integration for high-performance MoE, GEMM, and attention ops on AMD GPUs
Step-Video-T2V Inference with xDiT on AMD Instinct MI300X GPUs
Learn how to accelerate text-to-video generation using Step-Video-T2V, a 30B parameter T2V model, on AMD MI300X GPUs with ROCm—enabling scalable, high-fidelity video generation from text