
# Hungarian Recognizing Textual Entailment with Finetuned PULI BERT-Large Model

For further details, see [our demo site](https://juniper.nytud.hu/demo/nlp).

## Limitations

- max_seq_length = 350
- input format: {premise} [CLS] {hypothesis}

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

```
@inproceedings {yang-puli,
    title = {Jönnek a nagyok! BERT-Large, GPT-2 és GPT-3 nyelvmodellek magyar nyelvre},
	booktitle = {XIX. Magyar Számítógépes Nyelvészeti Konferencia (MSZNY 2023)},
	year = {2023},
	publisher = {Szegedi Tudományegyetem, Informatikai Intézet},
	address = {Szeged, Hungary},
	author = {Yang, Zijian Győző and Dodé, Réka and Ferenczi, Gergő and Héja, Enikő and Jelencsik-Mátyus, Kinga and Kőrös, Ádám and Laki, László János and Ligeti-Nagy, Noémi and Vadász, Noémi and Váradi, Tamás},
	pages = {247--262}
}
```
{"language": ["hu"], "license": "cc-by-nc-4.0", "tags": ["text-classification"], "datasets": ["NYTK/HuRTE"], "widget": [{"text": "Az els\u0151 Barbie bab\u00e1t 3 doll\u00e1r\u00e9rt adt\u00e1k el. [CLS] Az els\u0151 Barbie 3 doll\u00e1rba ker\u00fclt."}]}
transformers pytorch megatron-bert text-classification hu dataset:NYTK/HuRTE license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #megatron-bert #text-classification #hu #dataset-NYTK/HuRTE #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 


# Hungarian Recognizing Textual Entailment with Finetuned PULI BERT-Large Model

For further details, see our demo site.

## Limitations

- max_seq_length = 350
- input format: {premise} [CLS] {hypothesis}

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


# Hungarian Recognizing Textual Entailment with Finetuned PULI BERT-Large Model

For further details, see our demo site. ## Limitations

- max_seq_length = 350
- input format: {premise} [CLS] {hypothesis}

If you use this model, please cite the following paper:
TAGS
#transformers #pytorch #megatron-bert #text-classification #hu #dataset-NYTK/HuRTE #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # Hungarian Recognizing Textual Entailment with Finetuned PULI BERT-Large Model

For further details, see our demo site. ## Limitations

- max_seq_length = 350
- input format: {premise} [CLS] {hypothesis}

If you use this model, please cite the following paper:
TAGS
#transformers #pytorch #megatron-bert #text-classification #hu #dataset-NYTK/HuRTE #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 
# Hungarian Recognizing Textual Entailment with Finetuned PULI BERT-Large Model

For further details, see our demo site.## Limitations

- max_seq_length = 350
- input format: {premise} [CLS] {hypothesis}

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