pytorch bert text-classification transformers license:cc-by-4.0
---
license: cc-by-4.0
widget:
- text: "Study: Shifts in electricity generation spur net job growth, but coal jobs decline - via @DukeU https://www.eurekalert.org/news-releases/637217"
  example_title: "All categories"
- text: "Shifts in electricity generation spur net job growth, but coal jobs decline"
  example_title: "Only Cat 1.1"
- text: "Study on impacts of electricity generation shift via @DukeU https://www.eurekalert.org/news-releases/637217"
  example_title: "Only Cat 1.2 and 1.3"
- text: "@DukeU received grant for research on electricity generation shift"
  example_title: "Only Cat 1.3"
---
This SciBert-based multi-label classifier, trained as part of the work "SciTweets - A Dataset and Annotation Framework for Detecting Scientific Online Discourse", distinguishes three different forms of science-relatedness for Tweets. See details at https://github.com/AI-4-Sci/SciTweets .