Posts tagged AAC

Accelerating XGBoost with Dask using multiple AMD GPUs

XGBoost is an optimized library for distributed gradient boosting. It has become the leading machine learning library for solving regression and classification problems. For a deeper dive into how gradient boosting works, we recommend reading Introduction to Boosted Trees.

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LLM distributed supervised fine-tuning with JAX

In this article, we review the process for fine-tuning a Bidirectional Encoder Representations from Transformers (BERT)-based large language model (LLM) using JAX for a text classification task. We explore techniques for parallelizing this fine-tuning procedure across multiple AMD GPUs, then evaluate our model’s performance on a holdout dataset. For this, we use a (BERT)-base-cased transformer model with a General Language Understanding Evaluation (GLUE) benchmark dataset on multiple AMD GPUs.

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Pre-training a large language model with Megatron-DeepSpeed on multiple AMD GPUs

In this blog, we show you how to pre-train a GPT-3 model using the Megatron-DeepSpeed framework on multiple AMD GPUs. We also demonstrate how to perform inference on the text-generation task with your pre-trained model.

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