This training (in English) is dedicated to the multi-GPU scaling of the training of a Deep Learning model. The common thread of the practical aspects of the training is the optimized scaling (acceleration, distribution) of a model training on the ImageNet dataset, in PyTorch. For this, participants will be led to code and submit their […]
35 events found.
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2 events,This training aims to equip participants with the essential skills to adapt and effectively use Large Language Models (LLMs). It covers the main model adaptation techniques, including fine-tuning, Prompt Engineering, Retrieval-Augmented Generation (RAG), Parameter-Efficient Fine-Tuning (PEFT), and model alignment. The course also introduces multimodality and agentic systems, two key concepts for designing advanced LLM-based applications. […] |
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