Live broadcast: https://www.youtube.com/watch?v=EV7SkhRxemA How can you show what a Machine Learning model does once it's trained? In this talk, you're going to learn how to create Machine Learning apps and demos using Streamlit and Gradio, Python libraries for this purpose. Additionally, we'll see how to share them with the rest of the Open Source ecosystem. Learning to create graphic interfaces for models is extremely useful for sharing with other people interesting with them.
How can you show what a Machine Learning model does once it's trained? In this talk, you're going to learn how to create Machine Learning apps and demos using Streamlit and Gradio, Python libraries for this purpose. Additionally, we'll see how to share them with the rest of the Open Source ecosystem. Learning to create graphic interfaces for models is extremely useful for sharing with other people interesting with them. Some demo examples are: - https://huggingface.co/spaces/flax-community/dalle-mini - https://huggingface.co/spaces/flax-community/chef-transformer - https://huggingface.co/spaces/nielsr/LayoutLMv2-FUNSD
Speakers: Omar Sanseviero