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Large Language Models for Developers - from zero to your first LLM application

Material for the omonymous talk.

📝 Abstract The rise of ChatGPT and Large Language Models has revolutionized the tech landscape, leaving developers overwhelmed by the infinite opportunities and intrigued by the technical challenges posed by their complex nature.

This session provides a developer-centric introduction to LLMs, focused on practical applications.No pre-existing knowledge of LLMs and NLP is required.

You will gain insights into: using closed and open-source models, how to effectively prompt LLMs, vector databases, implementing Retrieval Augmented Generation applications (answer generation based on your data), building more complex applications.

Through a hands-on approach, I will show code examples using open-source tools: Haystack LLM framework, Hugging Face Transformers, Ollama, and more. I will also show how you can switch from proprietary to open models.

📚 Resources and code ‍💻

Haystack LLM framework

Start from a proprietary model

Switch to local open LLMs with Ollama

Chat with Mistral

Prompt Engineering

RAG

Naive RAG

Web RAG

Retrieval

Document Stores and Retrievers

Keyword-based Retrieval (BM25)

Embedding/vector Retrieval

Hybrid Retrieval

From Demo to Production

Choose a good Language Model

Choose a LLM inference solution

Evaluation

Deployment

Beyond RAG...

There is much more!

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