from malaya.supervised.huggingface import load
from malaya.torch_model.huggingface import IsiPentingGenerator
available_huggingface = {
'mesolitica/finetune-isi-penting-generator-t5-small-standard-bahasa-cased': {
'Size (MB)': 242,
'ROUGE-1': 0.24620333,
'ROUGE-2': 0.05896076,
'ROUGE-L': 0.15158954,
'Suggested length': 1024,
},
'mesolitica/finetune-isi-penting-generator-t5-base-standard-bahasa-cased': {
'Size (MB)': 892,
'ROUGE-1': 0.24620333,
'ROUGE-2': 0.05896076,
'ROUGE-L': 0.15158954,
'Suggested length': 1024,
},
}
info = """
tested on semisupervised summarization on unseen AstroAwani 20 news, https://github.com/huseinzol05/malay-dataset/tree/master/summarization/semisupervised-astroawani
each news compared ROUGE with 5 different generated texts.
"""
[docs]def huggingface(
model: str = 'mesolitica/finetune-isi-penting-generator-t5-base-standard-bahasa-cased',
force_check: bool = True,
**kwargs,
):
"""
Load HuggingFace model to generate text based on isi penting.
Parameters
----------
model: str, optional (default='mesolitica/finetune-isi-penting-generator-t5-base-standard-bahasa-cased')
Check available models at `malaya.generator.isi_penting.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.IsiPentingGenerator
"""
if model not in available_huggingface and force_check:
raise ValueError(
'model not supported, please check supported models from `malaya.generator.isi_penting.available_huggingface`.'
)
return load(
model=model,
class_model=IsiPentingGenerator,
available_huggingface=available_huggingface,
force_check=force_check,
path=__name__,
**kwargs,
)