Text Classification
Transformers
Safetensors
English
roberta
social-science
computational-social-science
situation-entity
genericity
discourse-modes
isaac
disco
Eval Results (legacy)
text-embeddings-inference
Instructions to use ISAAC-corpus/isaac-generalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ISAAC-corpus/isaac-generalization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ISAAC-corpus/isaac-generalization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ISAAC-corpus/isaac-generalization") model = AutoModelForSequenceClassification.from_pretrained("ISAAC-corpus/isaac-generalization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Cite the arXiv preprint (2609.27059)
Browse files
README.md
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```bibtex
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@article{hemmatian2026isaac,
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```
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```bibtex
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@article{hemmatian2026isaac,
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author = {Hemmatian, Babak and Hadjarab, Sarah and Chen, Jessica and Kurdi, Benedek},
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title = {The {Illinois} Social Attitudes Aggregate Corpus ({ISAAC}): An Open Tool and Reproducible Pipeline for Analyzing Social Group Discourse at Scale},
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year = {2026},
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journal = {arXiv},
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eprint = {2609.27059},
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archivePrefix = {arXiv},
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primaryClass = {cs.CL},
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doi = {10.48550/arXiv.2609.27059},
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url = {https://arxiv.org/abs/2609.27059}
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}
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```
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