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Building AI Agents with LLMs
Large language models are the reasoning units behind business-ready AI agents. Learn how they drive decisions and actions in a Compound AI system
By
The deepset Team
Fine-tuning Large Language Models
When is it useful – and when should you use other techniques like retrieval augmented generation (RAG) to improve your large language model’s (LLM's) output?
AI Fundamentals
AI Best Practices
Detecting Hallucinations in deepset
Our new node verifies if an LLM’s answers are grounded in facts
AI Best Practices
Solutions
AI Architecture
Document Search: The Art of Finding
A friendly introduction to search, retrieval, and their role in the large language model (LLM) era
AI Fundamentals
What Is Retrieval Augmented Generation?
Why retrieval augmented generation (RAG) is the key to safer applications with large language models (LLMs)
AI Architecture
AI Fundamentals
Best Practices in Deploying NLP Models
Read about best practices of deploying NLP models and establishing an effective, iterative style of NLP development.
AI Best Practices
The Implementation Cycle in Applied Natural Language Processing (NLP)
How to build winning applications using natural language processing (NLP): a practical guide
AI Best Practices
Build a Search Engine with GPT-3
Combine the power of large language models with a corpus of your choice to generate natural-sounding answers that are grounded in facts
AI Architecture
The Definitive Guide to BERT Models
The BERT language model greatly improved the standard for language models. This article explains BERT’s history and the language models derived from it.
