Introduction
Hugging Face is a popular platform for the AI and machine learning community. It allows developers, researchers, and AI enthusiasts to share machine learning models, datasets, and applications with others. Users can create repositories, upload files, and showcase their AI projects through the platform. If you are new to Hugging Face and want to learn how to upload and publish your content, this simple guide will help you understand the basic steps.
What Type of Content Can You Publish?
You can share:
- AI and machine learning models
- Datasets
- AI project files
- Machine learning demos
- Research-related resources
- Application examples
Step-by-Step Guide to Publish on Hugging Face
Step 1: Open Hugging Face
- Go to the Hugging Face website in your web browser.
- Click on Sign Up to create a new account using your email address if you do not have one, or click Log In if you already have an existing account and complete the authentication process.
Step 2: Select Content Type
From the dropdown menu under + New, choose your repository type based on your requirement. Select Model to upload and host a trained machine learning model, Dataset to store structured datasets or data files, Space to create and host interactive demos using Streamlit, Gradio, or Docker, or choose Bucket or Collection to organize resources and manage large objects. After selecting an option, you will be redirected to the repository configuration page to complete the setup.
Step 3: Slecte Model Repository
On this page, first enter your repository name in the Model name box, then click on the License field and select apache-2.0 or MIT. Choose your preferred visibility option (Public or Private), scroll down, and click the Create Model button to create your repository.
Step 4: Upload Files and Update Model Card
Your model repository manshi321 has been successfully created. Now, you can click on the Edit Model Card button to add your model description and details, or go to the Files and versions tab to directly upload your model files and weights through the web browser.
Step 4: Edit and Commit Model Card
Add your model details by selecting options like language, base_model, or pipeline_tag from the top section. In the editor box below, write a short overview or documentation about your model. Keep the Commit directly to the main branch option selected, then click Commit changes to main at the bottom-left corner to save your changes.
Step 8: Publish Your Content
Once everything is ready, save your changes and publish your repository. Your model, dataset, or Space will become available according to your selected visibility settings.
