The science team at Hugging Face reproduced and open source the seek r1. https://buff.ly/4jtbp8x

quiz app https://buff.ly/4atPzxo
dataset with questions https://buff.ly/3ClY9Sm
agents course we're working on https://buff.ly/4gehzqi

Here's how it works:

- make a dataset of multiple choice questions
- duplicate the space add set the dataset repo
- log in and do the quiz
- submit the questions to create a new dataset

I made this to get ready for the agents course, but I hope it's useful for you projects too!

Here's a blog post I wrote with the details https://buff.ly/4gVpudi

Here's a collection with tools for:

- create a plotly visualisation
- get travel duration
- transcribe youtube video
- transform image

https://buff.ly/3PAU6od

These should setup a few cool agent application, but if not it's easy to build a tool within a gradio application. Here's a guide:

https://buff.ly/3Wm2ZG1

Here's the chapter on agent in smol course: https://buff.ly/3Cf5NOf

❓What we need now?
Most of use aren't building systems to solve frontier math problems on a daily basis. Shucks! That means we need reward models and representative datasets that represent the kinds of problems we're trying to solve. Crucially, in the domains and languages we're actually working!

⏩ What does it mean for us builders?
As these approaches develop, we can use small models on our use cases, and increase inference for challenging domain specific tasks. This means that for most tasks models need minimal compute, but for complex tasks we'll scale up compute.