EuroCC@Greece HPC Training Series - Course 9 "Running LLMs on HPC: Transformers, Inference & Deployment"

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
Online
Live (synchronous)

Venue Information

Country: Greece
Venue Details: Click here

Training Content and Scope

Level of Instruction
Beginner
Intermediate
Advanced
Other
Sector of the Target Audience
Research and Academia
Industry
Public Sector
Other (general public...)
HPC Profile of Target Audience
Application Developers
Language of Instruction

Other Information

Organiser
Supporting Project(s)
EuroCC2/CASTIEL2
Event/Course Description

EuroCC@Greece announces the 9th Course of HPC Training Series with the subject "Running LLMs on HPC: Transformers, Inference & Deployment", taking place online on January 17th, 2025. 

Date: January 17th, 2025, at 10:00 EET (9:00 CET)

Location: Online via Zoom

Presentation Languages: Greek & English

Audience:

  • Data scientists and machine learning engineers.  
  • NLP researchers and practitioners.  
  • HPC system administrators and engineers.  
  • Developers exploring Hugging Face Transformers and RAG.  
  • Academic researchers working on language modeling projects.  
  • Professionals interested in training or deploying LLMs on HPC.  
  • Organizations planning to adopt HPC for AI workloads.

Description: This course focuses on Large Language Models running on High-Performance Computing systems. Gain a foundational understanding of the Hugging Face Transformers library, embeddingsmodels, and of Retrieval-Augmented Generation. Discover how to effectively set up an inference server on HPC systems as well as a deployment process and limitations. Training of the Greek LLM Meltemi will also be presented. This seminar will include hands-on sessions where users will be able to run the provided code.

Learning Objectives:

  • Hands-on experience on Hugging Face Transformers 
  • Set up and troubleshoot LLM inference servers on HPC systems.  
  • Explore LLM deployment on HPC, including limitations and applications.  
  • Learn the training process of the Greek LLM Meltemi.  
  • Understand capacity and scaling challenges in LLM deployment.  
  • Experiment with real-world applications of LLMs.

Prerequisites:

  • Basic understanding of machine learning and neural networks,
  • Knowledge of Python programming,
  • Basic command-line and Linux skills.

Note: Please enter your institutional/corporate email when registering