ConfliBERT Tasks and Applications
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Explore how ConfliBERT is applied across different NLP tasks such as Named Entity Recognition, Classification, and Multi-label Classification. • 4 items • Updated
# 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")Quick Links
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
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eventdata-utd/conflibert-binary-classification")