from malaya.supervised.huggingface import load
from malaya.torch_model.huggingface import Constituency
import logging
logger = logging.getLogger(__name__)
available_huggingface = {
'mesolitica/constituency-parsing-t5-small-standard-bahasa-cased': {
'Size (MB)': 247,
'Recall': 81.62,
'Precision': 83.32,
'FScore': 82.46,
'CompleteMatch': 22.40,
'TaggingAccuracy': 94.95,
},
'mesolitica/constituency-parsing-t5-base-standard-bahasa-cased': {
'Size (MB)': 545,
'Recall': 82.23,
'Precision': 82.12,
'FScore': 82.18,
'CompleteMatch': 23.50,
'TaggingAccuracy': 94.69,
}
}
info = """
Tested on https://github.com/aisingapore/seacorenlp-data/tree/main/id/constituency test set.
""".strip()
[docs]def huggingface(
model: str = 'mesolitica/constituency-parsing-t5-small-standard-bahasa-cased',
force_check: bool = True,
**kwargs,
):
"""
Load HuggingFace model to Constituency parsing.
Parameters
----------
model: str, optional (default='mesolitica/constituency-parsing-t5-small-standard-bahasa-cased')
Check available models at `malaya.constituency.available_huggingface`.
force_check: bool, optional (default=True)
Force check model one of malaya model.
Set to False if you have your own huggingface model.
Returns
-------
result: malaya.torch_model.huggingface.Constituency
"""
logger.warning(
'`malaya.constituency.huggingface` trained on indonesian dataset, not an actual malay dataset.')
return load(
model=model,
class_model=Constituency,
available_huggingface=available_huggingface,
force_check=force_check,
path=__name__,
**kwargs,
)
