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---
license: apache-2.0
language:
- hu
tags:
- text2text-generation
metrics:
- accuracy
widget:
- text: 'morph: munka NOUN Case=Acc|Number=Sin'
---
# Hungarian morphological generator model with mT5
For further models, scripts and details, see [our demo site](https://juniper.nytud.hu/demo/nlp).
- Pretrained model used: mT5
- Prefix: "morph: "
- UD-based generation
## Limitations
- max_source_length = 64
- max_target_length = 32
## Results
| Model | emMorph | UD |
| ------------- | ------------- | ------------- |
| mT5 | 95.53 | 94.66 |
## Usage with pipeline
```python
from transformers import pipeline
text2text_generator = pipeline(task="text2text-generation", model="NYTK/morphological-generator-ud-mt5-hungarian")
print(text2text_generator("morph: munka NOUN Case=Acc|Number=Sin")[0]["generated_text"])
```
## Citation
If you use this model, please cite the following paper:
```
@inproceedings {morph-generator,
title = {Neural Morphological Generators for Hungarian},
booktitle = {XIX. Magyar Számítógépes Nyelvészeti Konferencia (MSZNY 2023)},
year = {2023},
publisher = {Szegedi Tudományegyetem, Informatikai Intézet},
address = {Szeged, Hungary},
author = {Laki, László János and Ligeti-Nagy, Noémi and Vadász, Noémi and Yang, Zijian Győző},
pages = {331--340}
}
``` |