
## MODEL DESCRIPTION

huBERT base model (cased) fine-tuned on SQuAD v1
- huBert model + Tokenizer: https://huggingface.co/SZTAKI-HLT/hubert-base-cc
- Hungarian SQUAD v1 dataset: Machine Translated SQuAD dataset (Google Translate API)
- This is a demo model. Date of publication: 2022.03.27.

## Model in action

- Fast usage with pipelines:

```python
from transformers import pipeline
qa_pipeline = pipeline(
    "question-answering",
    model="mcsabai/huBert-fine-tuned-hungarian-squadv1",
    tokenizer="mcsabai/huBert-fine-tuned-hungarian-squadv1"
)
predictions = qa_pipeline({
    'context': "Anita vagyok és Budapesten élek már több mint 4 éve.",
    'question': "Hol lakik Anita?"
})
print(predictions)
# output:
# {'score': 0.9892364144325256, 'start': 16, 'end': 26, 'answer': 'Budapesten'}
```

{"language": "hu", "tags": ["question-answering", "bert"], "widget": [{"text": "Melyik foly\u00f3 szeli kett\u00e9 Budapestet?", "context": "Magyarorsz\u00e1g f\u0151v\u00e1ros\u00e1t, Budapestet a Duna foly\u00f3 szeli kett\u00e9. A XIX. sz\u00e1zadban \u00e9p\u00fclt L\u00e1nch\u00edd a dimbes-dombos budai oldalt k\u00f6ti \u00f6ssze a s\u00edk Pesttel. A V\u00e1rdomb oldal\u00e1ban fut\u00f3 sikl\u00f3val juthatunk fel a budai \u00d3v\u00e1rosba, ahol a Budapesti T\u00f6rt\u00e9neti M\u00fazeum eg\u00e9szen a r\u00f3mai id\u0151kig visszavezetve mutatja be a v\u00e1rosi \u00e9letet. A Szenth\u00e1roms\u00e1g t\u00e9r ad otthont a XIII. sz\u00e1zadi M\u00e1ty\u00e1s-templomnak \u00e9s a Hal\u00e1szb\u00e1stya l\u0151tornyainak, amelyekb\u0151l messzire ell\u00e1tva gy\u00f6ny\u00f6rk\u00f6dhet\u00fcnk a v\u00e1rosban."}, {"text": "Mivel juthatunk fel az \u00d3v\u00e1rosba?", "context": "Magyarorsz\u00e1g f\u0151v\u00e1ros\u00e1t, Budapestet a Duna foly\u00f3 szeli kett\u00e9. A XIX. sz\u00e1zadban \u00e9p\u00fclt L\u00e1nch\u00edd a dimbes-dombos budai oldalt k\u00f6ti \u00f6ssze a s\u00edk Pesttel. A V\u00e1rdomb oldal\u00e1ban fut\u00f3 sikl\u00f3val juthatunk fel a budai \u00d3v\u00e1rosba, ahol a Budapesti T\u00f6rt\u00e9neti M\u00fazeum eg\u00e9szen a r\u00f3mai id\u0151kig visszavezetve mutatja be a v\u00e1rosi \u00e9letet. A Szenth\u00e1roms\u00e1g t\u00e9r ad otthont a XIII. sz\u00e1zadi M\u00e1ty\u00e1s-templomnak \u00e9s a Hal\u00e1szb\u00e1stya l\u0151tornyainak, amelyekb\u0151l messzire ell\u00e1tva gy\u00f6ny\u00f6rk\u00f6dhet\u00fcnk a v\u00e1rosban."}]}
transformers pytorch tf bert question-answering hu endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #bert #question-answering #hu #endpoints_compatible #region-us 


## MODEL DESCRIPTION

huBERT base model (cased) fine-tuned on SQuAD v1
- huBert model + Tokenizer: URL
- Hungarian SQUAD v1 dataset: Machine Translated SQuAD dataset (Google Translate API)
- This is a demo model. Date of publication: 2022.03.27.

## Model in action

- Fast usage with pipelines:



## MODEL DESCRIPTION

huBERT base model (cased) fine-tuned on SQuAD v1
- huBert model + Tokenizer: URL
- Hungarian SQUAD v1 dataset: Machine Translated SQuAD dataset (Google Translate API)
- This is a demo model. Date of publication: 2022.03.27. ## Model in action

- Fast usage with pipelines:
TAGS
#transformers #pytorch #tf #bert #question-answering #hu #endpoints_compatible #region-us 
 ## MODEL DESCRIPTION

huBERT base model (cased) fine-tuned on SQuAD v1
- huBert model + Tokenizer: URL
- Hungarian SQUAD v1 dataset: Machine Translated SQuAD dataset (Google Translate API)
- This is a demo model. Date of publication: 2022.03.27. ## Model in action

- Fast usage with pipelines:
passage: TAGS
#transformers #pytorch #tf #bert #question-answering #hu #endpoints_compatible #region-us 
## MODEL DESCRIPTION

huBERT base model (cased) fine-tuned on SQuAD v1
- huBert model + Tokenizer: URL
- Hungarian SQUAD v1 dataset: Machine Translated SQuAD dataset (Google Translate API)
- This is a demo model. Date of publication: 2022.03.27.## Model in action

- Fast usage with pipelines: