--- license: mit library_name: timm tags: - robotics - vision pipeline_tag: robotics --- # Dobb·E [Project webpage](https://dobb-e.com) · [Documentation (gitbooks)](https://docs.dobb-e.com) · [Paper](https://arxiv.org/abs/2311.16098) **Authors**: [Mahi Shafiullah*](https://mahis.life), [Anant Rai*](https://raianant.github.io/), [Haritheja Etukuru](https://haritheja.com/), [Yiqian Liu](https://www.linkedin.com/in/eva-liu-ba90a5209/), [Ishan Misra](https://imisra.github.io/), [Soumith Chintala](https://soumith.ch), [Lerrel Pinto](https://lerrelpinto.com) Open-source repository of the Home Pretrained Representation (HPR) of [Dobb·E](https://dobb-e.com) and the associated paper, [On Bringing Robots Home](https://arxiv.org/abs/2311.16098) ## What's on this repo You can find our [Home Pretrained Models (HPR)](https://dobb-e.com/#models), which is a ResNet34 model trained on our dataset, [Homes of New York (HoNY)](https://dobb-e.com/#dataset), in this repo. You can download the weights if you want, or you can get started by using [Timm](https://huggingface.co/docs/timm/index). ```python import timm model = timm.create_model("hf_hub:notmahi/dobb-e", pretrained=True) ``` You can read more about it on our [paper](https://arxiv.org/abs/2311.16098) or our [website](https://dobb-e.com). Let's bring some robots home!