Share Your Detection & Pose Model On Hugging Face!

Hey guys! Niels from the Hugging Face open-source team here. I stumbled upon Fischer-Tom's awesome work on Arxiv about a unified category-level object detection and pose estimation model, and I'm super excited to share how we can make it even more accessible to the community! Let's dive in!

Improve Discoverability with Hugging Face Papers

First off, Fischer-Tom, have you considered submitting your paper to hf.co/papers? It's a fantastic way to boost the visibility of your research. The platform is designed to let researchers like you showcase your work and connect with a wider audience. Think of it as your paper's own little corner of the internet where people can discuss, explore, and, most importantly, find your amazing models!

Submitting is a breeze – just head over to https://huggingface.co/papers/submit if you're one of the authors. Once your paper is up, you can even claim it as your own, which adds it to your public profile on Hugging Face. This is a great way to build your reputation and connect your work directly to your online presence. Plus, you can add links to your GitHub repo and project page, making it super easy for others to delve deeper into your research and replicate your results. This is crucial for ensuring your work has a lasting impact and contributes to the broader field of object detection and pose estimation. By making your research readily accessible, you're not only helping other researchers but also fostering collaboration and driving innovation in the field. The more people who can access and understand your work, the more likely it is to be cited and built upon in future studies. This creates a ripple effect, where your research has a much greater reach and influence than it would otherwise. So, don't hesitate to share your brilliant work with the world – the Hugging Face Papers platform is the perfect place to do it!

Host Your Model on Hugging Face Hub for Enhanced Visibility

But wait, there's more! Have you thought about hosting your pre-trained model on https://huggingface.co/models? Trust me, this is a game-changer for discoverability. The Hugging Face Model Hub is a thriving community of researchers and practitioners, and having your model there means it's more likely to be found and used by others. We can add all sorts of tags to your model card, so people can easily find it based on keywords, tasks, and other criteria. We can also link it directly to your paper page, creating a seamless connection between your research and its practical application. This means that anyone who stumbles upon your paper can immediately try out your model, and vice versa. It's a win-win situation!

Uploading your model is easier than you might think. We've got a handy guide here that walks you through the process step-by-step. If you're working with a custom PyTorch model, you can even use the PyTorchModelHubMixin class (https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin). This neat little class adds from_pretrained and push_to_hub methods to your model, making it super simple to upload and download. Imagine, with just a few lines of code, you can make your model available to the entire world! If you prefer a more hands-on approach, you can also upload your model directly through the Hugging Face UI or use the hf_hub_download tool (https://huggingface.co/docs/huggingface_hub/en/guides/download#download-a-single-file). No matter your preferred method, we've got you covered. And once your model is up, we can link it to your paper page (https://huggingface.co/docs/hub/en/model-cards#linking-a-paper), making it even easier for people to discover your amazing work. So, what are you waiting for? Let's get your model out there and start making a real impact!

Build a Demo with Spaces and ZeroGPU Grants

But let's take it one step further! Imagine being able to showcase your model in a live demo that anyone can try out. That's where Hugging Face Spaces (https://huggingface.co/spaces) comes in! Spaces are a super cool way to build interactive demos for your models. It's like giving people a hands-on experience with your research, allowing them to see exactly what it can do. And the best part? We can even provide you with a ZeroGPU grant (https://huggingface.co/docs/hub/en/spaces-gpus#community-gpu-grants), which gives you access to A100 GPUs for free! That's right, you can build a killer demo without having to worry about the cost of compute.

Think of the possibilities! You could create a Space that allows users to upload images and see your model in action, detecting objects and estimating their poses in real-time. This is an incredibly powerful way to showcase the capabilities of your model and attract potential users and collaborators. Plus, it's a great way to get feedback on your research and identify areas for improvement. Building a Space is surprisingly easy, even if you're not a coding whiz. We've got tons of tutorials and resources to help you get started, and the Hugging Face community is always there to lend a hand. So, if you're looking for a way to take your research to the next level, building a demo on Spaces is definitely the way to go. And with our ZeroGPU grants, there's really no reason not to give it a try! Let's work together to create a truly impressive showcase for your unified category-level object detection and pose estimation model.

Let's Connect and Collaborate!

So, Fischer-Tom, what do you think? Are you as excited about these opportunities as I am? I'm here to help you every step of the way. Whether you're interested in submitting your paper, hosting your model, or building a demo, I'm happy to answer your questions and provide guidance. Let's connect and collaborate to make your research even more impactful! Feel free to reach out with any questions or concerns you might have. I'm looking forward to hearing from you and working together to bring your amazing work to the world. Let's make some AI magic happen!

Kind regards,

Niels