Journalists on Hugging Face

community

AI & ML interests

Democratizing access to useful AI tools and resources for journalists

Welcome to Journalists on Hugging Face, a community exploring the intersection of journalism and AI in the spirit of openness and collaboration. Here, we aim to share knowledge, tools, models, datasets, and projects to help news professionals discover useful resources to inform their reporting on or with the technology.

🧑‍🤝‍🧑 Join us (by tapping the button in the top right 😉) in shaping the future of journalism and AI.

💬 Regularly check in on the Community Tab to share projects, ask questions, get feedback, or report an issue.
You can also adjust your settings to receive notifications for new discussions.

👀 Take a peek at our collections at the bottom of this page for handy AI tools.

We’ve also curated some great links for you below:

🤗 Assistants

Assistants are a great way to configure models to perform specific tasks. We provide two helpful examples for journalists:

The prompts behind them are public. Feel free to tailor them to your needs. Also, share your ideas for other Assistants in the Community tab!

🛠️ Resources

  • Open Source Models with Hugging Face - In this course from DeepLearning.AI & 🤗, you’ll select open source models from Hugging Face Hub to perform NLP, audio, image and multimodal tasks using the Hugging Face transformers library. Easily package your code into a user-friendly app that you can run on the cloud using Gradio and Hugging Face Spaces.
  • Practical AI for Investigative Journalism - A six-session series led by Jonathan Soma, Journalism Professor at Columbia, covering real-life use cases in journalism and featuring numerous open-source tools.
  • Wonder Tools - Jeremy Caplan, Director of Teaching and Learning at CUNY’s Newmark Graduate School of Journalism, curated a list of interesting Spaces with potential use cases in journalism.
  • Tasks - Explore demos, use cases, models, datasets, and more to get started with tasks in computer vision, NLP, audio, multimodal, and reinforcement learning.
  • 🤗 Courses - Learn about natural language processing (NLP), audio, computer vision, reinforcement learning and diffusion models.
  • Open-Source AI Cookbook - A collection of notebooks illustrating practical aspects of building AI applications and solving various machine learning tasks using open-source tools and models.
  • Ethics & Society at 🤗 - A lot of useful resources from the Ethics & Society Team.

More resources coming soon

People We’re Following

Ping us!

🙏

Thanks to Avijit Ghosh, Yacine Jernite and Irene Solaiman for their advice on building this community.

models

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datasets

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