Transformers-Tutorials

Why we included this project

Anyone working through the HuggingFace Transformers library will get a lot out of these PyTorch notebooks, since each one shows a complete task with a real model. You can fine-tune BERT for named entity recognition or multi-label text classification, or run inference with object detectors like DETR and segmentation models like CLIPSeg. The demos span vision, audio, and text, so the same library API patterns show up across domains instead of staying confined to one use case. Every notebook links back to the original research paper and opens directly in Colab, which makes them easy to run and tweak. For people who learn by adapting working code, that's a faster way to build confidence than reading the docs.