Instructions to use eventdata-utd/conflibert-binary-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eventdata-utd/conflibert-binary-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eventdata-utd/conflibert-binary-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eventdata-utd/conflibert-binary-classification") model = AutoModelForSequenceClassification.from_pretrained("eventdata-utd/conflibert-binary-classification") - Notebooks
- Google Colab
- Kaggle
metadata
license: gpl-3.0
Model Card for Model ID
Conflibert-binary-classification is built upon the foundational Conflibert model. Through rigorous fine-tuning, this enhanced model demonstrates superior capabilities in classifying between conflict and non-conflict events.
- Finetuned from model : eventdata-utd/ConfliBERT-scr-uncased
- Paper : ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence
- Demo : Colab Notebook