Instructions to use sschellhammer/SciTweets_SciBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sschellhammer/SciTweets_SciBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sschellhammer/SciTweets_SciBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sschellhammer/SciTweets_SciBert") model = AutoModelForSequenceClassification.from_pretrained("sschellhammer/SciTweets_SciBert") - Notebooks
- Google Colab
- Kaggle
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 .
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