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Lecture: Unlock Your LLM's Potential with DSPy

An introduction to DSPy

A brief introduction to DSPy with hands-on showcases: use ML to optimize your prompts and setup a full pipeline to orchestrate several LMs.

DSPy is a groundbreaking framework designed to optimize the performance of language models (LMs) by refining prompts and weights algorithmically, especially within complex pipelines. Traditionally, using LMs within pipelines required a laborious process of isolating steps, crafting effective prompts, and fine-tuning for cohesion and accuracy. However, this approach was prone to inefficiencies and required manual adjustments with every change.

DSPy revolutionizes this process by decoupling program flow from LM parameters and introducing novel optimizers. These optimizers, driven by LMs, fine-tune prompts and weights based on desired metrics. By leveraging DSPy, models like GPT-3.5 and T5-base can achieve enhanced reliability and performance, while minimizing failure patterns. DSPy's innovative approach shifts LMs and prompts into the background, enabling a systematic and data-driven optimization process. In essence, DSPy empowers users to achieve higher scores with fewer prompts, ushering in a new era of LM-driven problem-solving.

Info

Day: 2024-08-18
Start time: 15:15
Duration: 01:00
Room: HS8
Track: AI AI, captain - LLM, machine learning & Co
Language: en

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