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From Syntax to Strategy: Harnessing LMQL for Smarter, Streamlined LLMs

1,657.00

  • This is a live workshop, to be held online
  • You will get the workshop joining link after your purchase
  • ADaSci members can register for free

Description

Date: 24th Feb 2024

Time: 10 AM to 1 PM

 

Language Model Query Language (LMQL) represents a pivotal advancement in optimizing interactions with Large Language Models (LLMs). LMQL streamlines the process by providing an intuitive syntax that enables efficient querying and strategic control over LLMs. LMQL simplifies complex interactions with LLMs by offering syntax that automates tasks and optimizes outcomes. This innovative language facilitates both syntax-driven communication with LLMs and strategic implementation, ensuring more efficient and adaptable utilization of these powerful models. Join this workshop and take a deep dive into LMQL for streamlining the LLMs.

Major Outline

  1. LLM Power, Challenge, and LMQL’s Arrival
  2. Unlocking LMQL Syntax
  3. Automating Tasks with LMQL
  4. Strategic Control and Fine-tuning with LMQL
  5. Integrating LMQL with Existing Tools and Workflows
  6. Advanced LMQL Techniques and Future Potential
  7. Hands-on Project: Building Your First LMQL-powered Application

Learning Outcomes

  1. Master the fundamentals of LMQL syntax and its potential for streamlining LLM interactions.
  2. Develop skills in writing LMQL scripts to automate tasks and optimize LLM outputs.
  3. Gain an understanding of strategic control techniques with LMQL for guiding and fine-tuning LLMs.
  4. Get hands-on experience building and deploying your own LMQL-powered LLM applications.

Requirements

  1. Google Colab / Jupyter notebook
  2. Good speed internet connectivity

Instructor

Sourabh Mehta, Data Scientist at AIM