Hugging Face Transformers projects for B.Tech students — real examples

What students actually build

• Language and document-processing capstone projects at VSET commonly build on pretrained transformer models.
• Smart India Hackathon language problem statements are often addressed by adapting an existing pretrained model.

Labs and infrastructure

• The AICTE IDEA Lab provides GPU workstations, which is what fine-tuning and inference on transformer models require.
• Campus computing labs support lighter inference and evaluation work.

How VSET teaches Hugging Face Transformers

Hugging Face Transformers is a Python library that gives access to pretrained transformer models for language, vision and audio, along with tooling for fine-tuning and inference. At VSET it is applied tooling in the deep learning and natural language work of the CSE AI and ML specialisation. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• VSET offers B.Tech CSE with an AI and Machine Learning specialisation among its seven GGSIPU programmes.
• Deep learning and natural language coursework there covers transformer models, with Python libraries as the working tooling.
• Linear algebra and probability coursework supply the mathematics attention mechanisms rest on.
• Fine-tuning and inference work is applied through projects rather than as a separate GGSIPU subject.