Zhen (Tony) Zhao – Training Language Models to Identify Urgent Messages in Real-Time
www.pydata.org
Providing timely maternal healthcare in developing countries is a critical challenge. This talk demonstrates how data-driven solutions can bridge healthcare gaps and improve access to vital healthcare information for pregnant women, with user privacy in mind. To do so, we fine-tuned the Gemma-2 2 billion parameter instruction model on a synthetic dataset in order to detect whether user messages pertain to urgent or non-urgent maternal healthcare issues. By quickly identifying and prioritizing user inquiries, the model can aid help desks by ensuring urgent messages are promptly forwarded to the appropriate healthcare professionals for immediate intervention.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
