Agentic Conversations (formally mlops.community)
Agentic Conversations (formally mlops.community)
Demetrios
Handling Multi-Terabyte LLM Checkpoints // Simon Karasik // #228
55 minutes Posted Apr 30, 2024 at 5:57 pm.
] Simon preferred beverage
] Takeaways
] Simon's tech background
] Zombie models garbage collection
] The road to LLMs
] Trained models Simon worked on
] LLM Checkpoints
] Confidence in AI Training
] Different Checkpoints
] Checkpoint parts
] Slurm vs Kubernetes
] Storage choices lessons
] Paramount components for setup
] Argo workflows
] Kubernetes node troubleshooting
] Cloud virtual machines have pre-installed mentoring
] Fine-tuning
] Storage, networking, and complexity in network design
] Start simple before advanced; consider model needs.
] Join us at our first in-person conference on June 25 all about AI Quality
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Join us at our first in-person conference on June 25 all about AI Quality: https://www.aiqualityconference.com
Simon Karasik⁠ is a proactive and curious ML Engineer with 5 years of experience. Developed & deployed ML models at WEB and Big scale for Ads and Tax.
Huge thank you to Nebius AI for sponsoring this episode. Nebius AI - https://nebius.ai/
MLOps podcast #228 with Simon Karasik, Machine Learning Engineer at Nebius AI, Handling Multi-Terabyte LLM Checkpoints.
// Abstract
The talk provides a gentle introduction to the topic of LLM checkpointing: why is it hard, how big are the checkpoints. It covers various tips and tricks for saving and loading multi-terabyte checkpoints, as well as the selection of cloud storage options for checkpointing.
// Bio
Full-stack Machine Learning Engineer, currently working on infrastructure for LLM training, with previous experience in ML for Ads, Speech, and Tax.
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// Related Links
--------------- ✌️Connect With Us ✌️ -------------
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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Simon on LinkedIn: https://www.linkedin.com/in/simon-karasik/
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