Text Classification
Transformers
Safetensors
English
bibr
OECD
scientific-paper-classification
MiniLM
Instructions to use scienceverse/bibr-paper-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scienceverse/bibr-paper-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scienceverse/bibr-paper-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("scienceverse/bibr-paper-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "l1_classes": [ | |
| "Agricultural and Veterinary Sciences", | |
| "Engineering and Technology", | |
| "Humanities and the Arts", | |
| "Medical and Health Sciences", | |
| "Natural Sciences", | |
| "Social Sciences" | |
| ], | |
| "l2_classes": [ | |
| "Agriculture, Forestry, and Fisheries", | |
| "Animal and Dairy Science", | |
| "Arts (arts, history of arts, performing arts, music)", | |
| "Basic Medicine", | |
| "Biological Sciences", | |
| "Chemical Engineering", | |
| "Chemical Sciences", | |
| "Civil Engineering", | |
| "Clinical Medicine", | |
| "Computer and Information Sciences", | |
| "Earth and Related Environmental Sciences", | |
| "Economics and Business", | |
| "Education", | |
| "Electrical Engineering, Electronic Engineering, Information Engineering", | |
| "Environmental Engineering", | |
| "Health Sciences", | |
| "History and Archaeology", | |
| "Languages and Literature", | |
| "Law", | |
| "Materials Engineering", | |
| "Mathematics", | |
| "Mechanical Engineering", | |
| "Media and Communications", | |
| "Medical Biotechnology", | |
| "Medical Engineering", | |
| "Philosophy, Ethics and Religion", | |
| "Physical Sciences", | |
| "Political Science", | |
| "Psychology and Cognitive Sciences", | |
| "Social and Economic Geography", | |
| "Sociology", | |
| "Veterinary Science" | |
| ], | |
| "paper_type_classes": [ | |
| "case-study", | |
| "commentary", | |
| "empirical", | |
| "erratum", | |
| "meta-analysis", | |
| "retraction", | |
| "review" | |
| ] | |
| } | |