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.