---
library_name: transformers
pipeline_tag: text-classification
language:
- cs
tags:
- legal
- czech
- modernbert
- legal-nlp
---

# ModernBERT-large-madon-formalism

This model is a companion for the paper [Mining Legal Arguments to Study Judicial Formalism](https://huggingface.co/papers/2512.11374). It is part of the **MADON** project, which aims to study judicial reasoning in the decisions of Czech Supreme Courts.

## Model Description
This model is based on the ModernBERT architecture and was adapted to the Czech legal domain through continued pretraining on a corpus of over 300,000 Czech court decisions. It is specifically fine-tuned for the **holistic formalism classification** of full legal documents, identifying whether a judicial decision is formalistic or non-formalistic.

- **Task:** Holistic formalism classification
- **Language:** Czech
- **Dataset:** MADON (Czech Supreme Court decisions)
- **Repository:** [trusthlt/madon](https://github.com/trusthlt/madon)

## Usage

If you want to use it for holistic formalism classification of Czech legal court documents, we suggest:

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

model = AutoModelForSequenceClassification.from_pretrained("TrustHLT/ModernBERT-large-madon-formalism")
tokenizer = AutoTokenizer.from_pretrained("TrustHLT/ModernBERT-large-madon-formalism")

pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)

# The expected input is a full Czech legal court document
text = "Dovolání se zamítá..." # Example Czech legal text

print(pipe(text))
```

## Citation
If you use this model or the MADON dataset in your research, please cite the following paper:

```bibtex
@article{madon2025mining,
  title={Mining Legal Arguments to Study Judicial Formalism},
  author={Kocián, Michal and Šavelka, Jaromír and Moravčík, Jakub and Gavenčiak, Tomáš and Harašta, Jakub and Štefánik, Michal},
  journal={arXiv preprint arXiv:2512.11374},
  year={2025}
}
```