tceron/wildseek
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How to use tceron/open-endedness-classifier with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="tceron/open-endedness-classifier") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("tceron/open-endedness-classifier")
model = AutoModelForSequenceClassification.from_pretrained("tceron/open-endedness-classifier", device_map="auto")This model classifies user interaction queries between Analytical and Factoid.
Label IDs:
0: "Analytical"
1: "Factoid"
All details in:
@inproceedings{ceron2026wildseek,
title = {WildSEEK: Evaluating Language Models for Information-Seeking},
author = {Ceron, Tanise and Baumann, Joachim and Bassignana, Elisa and Cabuk, Berat and Hovy, Dirk and Nozza, Debora},
booktitle = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing},
year = {2026}
}
tceron/info-seek-classifier — information seeking, content creation, coding, not english, no requesttceron/high-risk-classifier — Other, Economic and Financial, Health, Politics, Judicial and Legal, Moral Values and Religion, SecurityBase model
answerdotai/ModernBERT-large