Bigger isn’t always better. Train and tune highly focused language models optimized for domain specific tasks.

When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of a LLM may hurt more than it helps. Domain-Specific Small Language Models teaches you to build generative AI models optimized for specific fields.

In Domain-Specific Small Language Models you’ll discover:

Model sizing best practices
Open source libraries, frameworks, utilities and runtimes
Fine-tuning techniques for custom datasets
Hugging Face’s libraries for SLMs
Running SLMs on commodity hardware
Model optimization or quantization

Perfect for cost- or hardware-constrained environments, Small Language Models (SLMs) train on domain specific data for high-quality results in specific tasks. In Domain-Specific Small Language Models you’ll develop SLMs that can generate everything from Python code to protein structures and antibody sequences—all on commodity hardware.