1. Offer APIs to exercise various types of downstream tasks (like Table-Summary and Table-QA) on Tabular data.
2. Add support (into the platform) for trying with different types of LLMs available on HuggingFace (like IBM Granite models).
1. Understand various types downstream tasks for Tabular Data
2. Develop packages/libraries required to work with Tabular Data, which can be used in any application that deals with tabular data (along with other modes of data like text and images)
Tools-Technologies | Jupyter Python Notebooks, WatsonX.ai |
Platform | 1 ) WatsonX
|
College | All College |
Krishnasuri Narayanam' Comment
We are looking for Master students as preferred candidates.