DATA Pill #086 - Milk the LLM

Hi,

Today, we’ll dive deeper into everything you need to know about LLMs.

Are you ready? We’re starting now!?

ARTICLES

How to Build Data Analytics Using LLMs in Under 5 Minutes | 5 min | LLM | Patrik Braborec | GoodData Developers

GoodData has been a driving force in the data analytics scene, and now they're taking the lead in the LLMs era. They're making things more intuitive by automating analytics and letting users chat with their data in plain English. It's a game-changer, eliminating the need for technical know-how when asking questions and setting a new, user-friendly standard for data querying.

How to use LLMs for data enrichment in BigQuery | 16 min | LLM | Piotr Pilis | GetInData | Part of Xebia Blog

A comprehensive guide on how individuals can leverage LLMs and BigQuery to bring additional value to data and boost analytical capabilities. Use cases, architectural considerations, implementation steps and evaluation methods to ensure that readers are fully equipped to use this powerful combination in their own data processes.

LMQL — SQL for Language Models | 17 min | LLM | Mariya Mansurova | Towards Data Science Blog

This article explores LMQL's advantages in addressing challenges faced by LLMs, such as interaction complexity and token representation constraints. While acknowledging some limitations, the article touches on LMQL's potential benefits in offering nuanced control over output and reducing costs. Practical examples demonstrate LMQL's syntax and application in sentiment analysis tasks, using local models like Zephyr and Llama-2-7B, concluding with a nuanced evaluation of LMQL's performance and role in Language Model Programming.

In MORE LINKS you will read about: Getting the Most from LLMs: Building a Knowledge Brain for Retrieval Augmented Generation

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TUTORIALS

Running Mixtral 8x7b locally with LlamaIndex | 6 min | LlamaIndex Blog

Dive into the release, Mixtral 8x7b, which has stirred excitement by demonstrating its capabilities comparable to or surpassing GPT-3.5 and Llama2 70b on various benchmarks. LlamaIndex provides a step-by-step guide to incorporating Mixtral into your local environment. Explore how Mixtral can be seamlessly integrated into LlamaIndex, allowing you to harness its potential and run powerful AI models locally.?

Dataset enrichment using LLM’s | 7 min | Jeroen Overschie | Xebia Tech Blog

This tutorial? explores 3 strategies on how to use LLMs for extracting structured data from a piece of text by:

• providing a JSON example,
• defining a Pydantic schema (also see this blogpost),
• using OpenAI's Function Calling API.

In MORE LINKS you will read about: Getting the Most from LLMs: Building a Knowledge Brain for Retrieval Augmented Generation

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TOOLS

vLLM

vLLM is a fast and easy-to-use library for LLM inference and serving.

Ollama

Ollama is a tool for running AI models on your hardware. Many users will choose to use the Command Line Interface (CLI) to work with Ollama.

DATA TUBE

LlamaIndex Workshop: Multimodal + Advanced RAG Workhop with Gemini | 53 min | Cher Hu, Lawrence Tsang, Michael Chen | LlamaIndex

The Google Gemini release included both exciting multi-modal capabilities as well as semantic retrieval. In this workshop, we cover two cool LLM + RAG use cases with Google Gemini:

• Multi-modal RAG: Use the Gemini model to extract structured outputs from images. Then learn how to index these texts + images and build a QA system from it (also using Gemini).
• Advanced RAG: Learn how to use the brand-new Semantic Retrieval API. You can decompose it into different components - custom embedding-based retrieval and custom response synthesis.

PODCAST

Orchestration for LLM and RAG applications | 50 min | LLM | Ben Lorica and Malte Pietsch | The Data Exchange Podcast

Listen to the talk with Malte Pietsch, co-founder & CTO at Deepset who leads the development of Haystack, an open-source orchestration framework for Large Language Models (LLMs). This user-friendly tool streamlines the integration of LLMs, vector databases and document stores, making complex system development effortless.?

In MORE LINKS you will read about: Are LLMs the end of computer programming (as we know it)?

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Adam from the GetInData | Part of Xebia