Instructions to use tceron/open-endedness-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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")# pip install -U transformers accelerate # 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") - Notebooks
- Google Colab
- Kaggle
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Download README.md from tceron/open-endedness-classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.1 kB
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https://huggingface.co/tceron/open-endedness-classifier/resolve/main/README.md
- Command line
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hf download hf://tceron/open-endedness-classifier/README.md
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curl -L -o README.md https://huggingface.co/tceron/open-endedness-classifier/resolve/main/README.md
1.1 kB
metadata
library_name: transformers
license: odc-by
datasets:
- tceron/wildseek
language:
- en
metrics:
- f1
base_model:
- answerdotai/ModernBERT-large
pipeline_tag: text-classification
Model Card for Model ID
This model classifies user interaction queries between Analytical and Factoid.
Label IDs:
0: "Analytical"
1: "Factoid"
Model Details
All details in paper:
@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}
}
Other classifiers from this study are:
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, Security