pytorch

示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
280pytorch
This model is trained on 180G data, we recommend using this one than the original version. 示例代码 from
240pytorch
Chinese BERT with Whole Word Masking For further accelerating Chinese natural language processing, w
500pytorch
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
310pytorch
This is a re-trained 3-layer RoBERTa-wwm-ext model. Chinese BERT with Whole Word Masking For further
290pytorchbert
This model is trained on 180G data, we recommend using this one than the original version. Chinese E
210pytorch
This is a re-trained 3-layer RoBERTa-wwm-ext-large model. Chinese BERT with Whole Word Masking For f
270pytorchbert
This is a re-trained 6-layer RoBERTa-wwm-ext model. Chinese BERT with Whole Word Masking For further
290pytorchbert
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
240pytorch
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
260pytorch
Chinese Pre-Trained XLNet This project provides a XLNet pre-training model for Chinese, which aims t
240pytorch
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
280pytorch
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
290pytorch
Please use ElectraForPreTraining for discriminator and ElectraForMaskedLM for generator if you are r
290pytorch
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
310pytorchbert
Please use ElectraForPreTraining for discriminator and ElectraForMaskedLM for generator if you are r
250pytorch
Chinese Pre-Trained XLNet This project provides a XLNet pre-training model for Chinese, which aims t
320pytorch
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
310pytorchbert
示例代码 from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks pipelin
270pytorchbert
This model is trained on 180G data, we recommend using this one than the original version. 示例代码 from
270pytorch
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