# Big Transfer (BiT) **Big Transfer (BiT)** is a type of pretraining recipe that pre-trains on a large supervised source dataset, and fine-tunes the weights on the target task. Models are trained on the JFT-300M dataset. The finetuned models contained in this collection are finetuned on ImageNet. {% include 'code_snippets.md' %} ## How do I train this model? You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh. ## Citation ```BibTeX @misc{kolesnikov2020big, title={Big Transfer (BiT): General Visual Representation Learning}, author={Alexander Kolesnikov and Lucas Beyer and Xiaohua Zhai and Joan Puigcerver and Jessica Yung and Sylvain Gelly and Neil Houlsby}, year={2020}, eprint={1912.11370}, archivePrefix={arXiv}, primaryClass={cs.CV} } ```