Part 11/13:
- Custom Fine-Tuning Pipelines: Incorporating retrieval, masking, and error correction to curtail hallucinations and bias.
Participants were encouraged to experiment with open-source models, fine-tune their own, and integrate various tools for deployment, emphasizing the growing ecosystem of accessible AI.
Community and Resources
The event provided valuable resources, including links to official documentation, code repositories, and online forums. Attendees were advised on best practices for:
Prompt Engineering: Structuring prompts for consistency and safety.
Data Privacy: Handling enterprise data in private environments.
Model Optimization: Balancing cost, latency, and accuracy.