The Guide to Deploying LLMs for Real-World Deployments
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What's inside:
Learn practical tips and techniques to:
- Architect LLMs for your specific use case
- Optimize LLM infrastructure for scale and cost-efficiency Implement monitoring, logging, and maintenance workflows
- Employ ethical AI practices for transparency and bias mitigation
- Continuously benchmark, test, and improve LLMs over time
Whether you’re involved in developing, deploying or optimizing LLMs, this guide to deploying equips you with the operational knowledge to successfully run LLMs in production.
Who you'll hear from:
Andrew Wilson
Head of Solutions, Seldon
“LLM’s versatility enables them to be easily adaptable to new use cases beyond their original training objective.”
Sherif Akoush
MLOps Engineer, Seldon
“Careful optimization based on the use case is required to avoid overprovisioning expensive GPU hardware or hurting end users’ latencies.”
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