readme: ---
  license: apache-2.0
  language:
  - hu
  tags:
  - text2text-generation
  metrics:
  - accuracy
  widget:
  - text: 'morph: munka [/N][Acc]'
  ---
  
  # 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: "
    - emMorph-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-emmorph-mt5-hungarian")
  
  print(text2text_generator("morph: munka [/N][Acc]")[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}
  }
  ```