Metadata-Version: 2.1
Name: fastbert
Version: 0.0.8
Summary: The pipy version of FastBERT
Home-page: https://github.com/autoliuweijie/FastBERT
Author: Weijie Liu
Author-email: autoliuweijie@163.com
License: UNKNOWN
Description: # FastBERT-pypi
        
        The pypi version of [FastBERT](https://github.com/autoliuweijie/FastBERT).
        
        
        ## Install
        
        Install ``fastbert`` with ``pip``.
        ```sh
        $ pip install fastbert
        ```
        
        ## Single sentence classification
        
        An example of single sentence classification are shown in [single_sentence_classification](examples/single_sentence_classification/).
        
        ```python
        from fastbert import FastBERT
        
        # Loading your dataset
        labels = ['T', 'F']
        sents_train = [
            'Do you like FastBERT?',
            'Yes, it runs faster than BERT!',
            ...
        ]
        labels_train = [
            'T',
            'F',
            ...
        ]
        
        # Creating and training model
        model = FastBERT(
            kernel_name="google_bert_base_en",  # "google_bert_base_zh" for Chinese
            labels=labels,
            device='cuda:0'
        )
        
        model.fit(
            sents_train,
            labels_train,
            model_saving_path='./fastbert.bin',
        )
        
        # Loading model and making inference
        model.load_model('./fastbert.bin')
        label, exec_layers = model('I like FastBERT', speed=0.7)
        ```
        
        
        ## Two sentences classification
        
        ```python
        from fastbert import FastBERT_S2
        
        # Loading your dataset
        labels = ['T', 'F']
        questions_train = [
            'FastBERT快吗?',
            '你在业务里使用FastBERT了吗?',
            ...
        ]
        answers_train = [
            '快！而且速度还可调.',
            '用了啊，帮我省了好几百台机器.',
            ...
        ]
        labels_train = [
            'T',
            'T',
            ...
        ]
        
        # Creating and training model
        model = FastBERT_S2(
            kernel_name="google_bert_base_zh",  # "google_bert_base_en" for English
            labels=labels,
            device='cuda:0'
        )
        
        model.fit(
            sents_a_train=questions_train,
            sents_b_train=answers_train,
            labels_train=labels_train,
            model_saving_path='./fastbert.bin',
        )
        
        # Loading model and making inference
        model.load_model('./fastbert.bin')
        label, exec_layers = model(
            sent_a='我也要用FastBERT!',
            sent_b='来，吃老干妈!',
            speed=0.7)
        ```
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.4
Description-Content-Type: text/markdown
