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How to Run LLM Locally Using LM Studio?

Analytics Vidhya

In this article, we’ll dive into how to run an LLM locally using LM Studio. We’ll walk through the essential steps, explore potential challenges, […] The post How to Run LLM Locally Using LM Studio? One fantastic tool that makes this easier is LM Studio. appeared first on Analytics Vidhya.

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Efficient LLM Workflows with LangChain Expression Language

Analytics Vidhya

Introduction The advancements in LLM world is growing fast and the next chapter in AI application development is here. Initially known for proof-of-concepts, LangChain has rapidly evolved into a powerhouse Python library for LLM interactions. LangChain Expression Language (LCEL) isn’t just an upgradeā€”it’s a game-changer.

LLM 281
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Optimizing AI Performance: A Guide to Efficient LLM Deployment

Analytics Vidhya

To unlock such potential, businesses must master […] The post Optimizing AI Performance: A Guide to Efficient LLM Deployment appeared first on Analytics Vidhya. Imagine a world where customer service chatbots not only understand but anticipate your needs, or where complex data analysis tools provide insights instantaneously.

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How to Run LLM Models Locally with Ollama?

Analytics Vidhya

Enter Ollama, the platform that makes working with open-source LLMs a breeze. Imagine […] The post How to Run LLM Models Locally with Ollama? But let’s be honestā€”setting up your environment and getting these models to run smoothly on your machine can be a real headache. appeared first on Analytics Vidhya.

LLM 259
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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Join Travis Addair, CTO of Predibase, and Shreya Rajpal, Co-Founder and CEO at Guardrails AI, in this exclusive webinar to learn: How guardrails can be used to mitigate risks and enhance the safety and efficiency of LLMs, delving into specific techniques and advanced control mechanisms that enable developers to optimize model performance effectively (..)

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Guide to LLM Observability and Evaluations for RAG ApplicationĀ 

Analytics Vidhya

Introduction In the fast-evolving world of AI, it’s crucial to keep track of your API costs, especially when building LLM-based applications such as Retrieval-Augmented Generation (RAG) pipelines in production.

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Full Guide on LLM Synthetic Data Generation

Unite.AI

In this comprehensive guide, we'll explore LLM-driven synthetic data generation, diving deep into its methods, applications, and best practices. Introduction to Synthetic Data Generation with LLMs Synthetic data generation using LLMs involves leveraging these advanced AI models to create artificial datasets that mimic real-world data.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)

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How to Leverage AI for Actionable Insights in BI, Data, and Analytics

Learn how you can bring your own LLM or SLM and enhance your application with embedded analytics and BI powered by Logi Symphony. Imagine having an AI tool that answers your userā€™s questions with a deep understanding of the context in their business and applications, nuances of their industry, and unique challenges they face.