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Improving your LLMs with RLHF on Amazon SageMaker

AWS Machine Learning

Reinforcement Learning from Human Feedback (RLHF) is recognized as the industry standard technique for ensuring large language models (LLMs) produce content that is truthful, harmless, and helpful. For the purpose of this blog post, we’re using demonstration data in the HH dataset as reported above. yaml ppo_hh.py

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25 Call Center Leaders Share the Most Effective Ways to Boost Contact Center Efficiency

Callminer

Training documentation needs to be updated regularly, and on-going training is important for improving efficiency. Bill Dettering is the CEO and Founder of Zingtree , a SaaS solution for building interactive decision trees and agent scripts for contact centers (and many other industries). Bill Dettering. Jeff Greenfield.

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Average Handle Time: A Comprehensive Guide

Hodusoft

The term is known as ‘Average Handle Time’ and in this blog post, we will discuss it in detail. What’s the “standard” AHT for a call center? Post-call work time = the time an agent spent on post-call work after the ending of the call (for example researching, documenting, etc.) What’s the “standard” AHT for a call center?

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Accelerate your security and AI/ML learning with best practices guidance, training, and certification AWS also curates recommendations from Best Practices for Security, Identity, & Compliance and AWS Security Documentation to help you identify ways to secure your training, development, testing, and operational environments.

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Gemma is now available in Amazon SageMaker JumpStart 

AWS Machine Learning

. * The `if __name__ == "__main__"` block checks if the script is being run directly or imported. estimator.set_hyperparameters(chat_dataset="True", peft_type="lora", max_input_length="2048", epoch="3") estimator.fit({"training": }) Underlying the training scripts, JumpStart uses HuggingFace SFTTrainer with QLoRA and FlashAttention.

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Best practices to build generative AI applications on AWS

AWS Machine Learning

There are several use cases where RAG can help improve FM performance: Question answering – RAG models help question answering applications locate and integrate information from documents or knowledge sources to generate high-quality answers. The retrieved information provides useful context and ideas.

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18 Contact Center Strategies That Actually Work

JustCall

The best way is to work with industry-tested strategies that have proven themselves time and again. In this In this blog, we discuss the 18 crucial contact center strategies your business must work on to improve contact center performance. You can further categorize the scripts to help with a more extensive training session.