Source code for malaya.generator.isi_penting

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, )