Source code for malaya.summarization.abstractive

from malaya.supervised.huggingface import load
from malaya.torch_model.huggingface import Summarization

available_huggingface = {
    'mesolitica/finetune-summarization-t5-small-standard-bahasa-cased': {
        'Size (MB)': 242,
        'ROUGE-1': 0.75721802,
        'ROUGE-2': 0.496729027,
        'ROUGE-L': 0.304021823,
        'Suggested length': 1024,
    },
    'mesolitica/finetune-summarization-t5-base-standard-bahasa-cased': {
        'Size (MB)': 892,
        'ROUGE-1': 0.7132268255,
        'ROUGE-2': 0.470135011,
        'ROUGE-L': 0.366797009,
        'Suggested length': 1024,
    },
    'mesolitica/finetune-summarization-ms-t5-small-standard-bahasa-cased': {
        'Size (MB)': 242,
        'ROUGE-1': 0.742572468,
        'ROUGE-2': 0.50196339,
        'ROUGE-L': 0.3741226432,
        'Suggested length': 1024,
    },
    'mesolitica/finetune-summarization-ms-t5-base-standard-bahasa-cased': {
        'Size (MB)': 892,
        'ROUGE-1': 0.728116529,
        'ROUGE-2': 0.49656772621,
        'ROUGE-L': 0.376577199,
        'Suggested length': 1024,
    },
}

info = """
tested on translated validation set CNN Daily Mail, https://huggingface.co/datasets/mesolitica/translated-cnn-dailymail
tested on translated test set Xwikis, https://huggingface.co/datasets/mesolitica/translated-xwikis
""".strip()


[docs]def huggingface( model: str = 'mesolitica/finetune-summarization-t5-small-standard-bahasa-cased', force_check: bool = True, **kwargs, ): """ Load HuggingFace model to abstractive summarization. Parameters ---------- model: str, optional (default='mesolitica/finetune-summarization-t5-small-standard-bahasa-cased') Check available models at `malaya.summarization.abstractive.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.Summarization """ if model not in available_huggingface and force_check: raise ValueError( 'model not supported, please check supported models from `malaya.summarization.abstractive.available_huggingface`.' ) return load( model=model, class_model=Summarization, available_huggingface=available_huggingface, force_check=force_check, path=__name__, **kwargs, )