
# 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}
}
```
{"language": ["hu"], "license": "apache-2.0", "tags": ["text2text-generation"], "metrics": ["accuracy"], "widget": [{"text": "morph: munka NOUN Case=Acc|Number=Sin"}]}
transformers pytorch mt5 text2text-generation hu license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

Hungarian morphological generator model with mT5
================================================


For further models, scripts and details, see our demo site.


* Pretrained model used: mT5
* Prefix: "morph: "
* UD-based generation


Limitations
-----------


* max\_source\_length = 64
* max\_target\_length = 32


Results
-------


Model: mT5, emMorph: 95.53, UD: 94.66


Usage with pipeline
-------------------


If you use this model, please cite the following paper:



TAGS
#transformers #pytorch #mt5 #text2text-generation #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

TAGS
#transformers #pytorch #mt5 #text2text-generation #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
