This will be an introduction to platforms like Hugging Face, which calls itself “the AI community building the future”.
This platform enables developers to collaborate on over a million public models and datasets. This talk will highlight how Hugging Face embodies that FOSS advantage and how anyone can leverage its libraries to experiment with AI.
I will also introduce prompt engineering—the craft of writing natural-language instructions to guide a large language model’s output. A well-designed prompt can steer an open LLM to perform tasks.
Main pointers of the talk:
An overview of the Hugging Face ecosystem: pre-trained model hubs, datasets, and open-source libraries.
A demo of the utilisation of Hugging Face spaces.
Basics of prompt engineering: designing clear prompts to get valuable results from language models
This talk will give a gentle, hands-on introduction so attendees can use open-source AI models today.
Free and open AI tools empower developers by removing cost barriers and enabling collaboration.
Hugging Face provides a rich, community-driven library of open-source models and datasets for text, vision, audio, and more.
Prompt engineering is an easy way to tap into these models: even simple, well-crafted text prompts can produce powerful results.