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XLNet模型汇总
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下表汇总介绍了目前PaddleNLP支持的XLNet模型对应预训练权重。
关于模型的具体细节可以参考对应链接。

+----------------------------------------------------------------------------------+--------------+----------------------------------------------------------------------------------+
| Pretrained Weight                                                                | Language     | Details of the model                                                             |
+==================================================================================+==============+==================================================================================+
|``xlnet-base-cased``                                                              | English      | 12-layer, 768-hidden,                                                            |
|                                                                                  |              | 12-heads, 110M parameters.                                                       |
|                                                                                  |              | XLNet English model.                                                             |
+----------------------------------------------------------------------------------+--------------+----------------------------------------------------------------------------------+
|``xlnet-large-cased``                                                             | English      | 24-layer, 1024-hidden,                                                           |
|                                                                                  |              | 16-heads, 340M parameters.                                                       |
|                                                                                  |              | XLNet Large English model.                                                       |
+----------------------------------------------------------------------------------+--------------+----------------------------------------------------------------------------------+
|``chinese-xlnet-base``                                                            | Chinese      | 12-layer, 768-hidden,                                                            |
|                                                                                  |              | 12-heads, 117M parameters.                                                       |
|                                                                                  |              | XLNet Chinese model.                                                             |
+----------------------------------------------------------------------------------+--------------+----------------------------------------------------------------------------------+
|``chinese-xlnet-mid``                                                             | Chinese      | 24-layer, 768-hidden,                                                            |
|                                                                                  |              | 12-heads, 209M parameters.                                                       |
|                                                                                  |              | XLNet Medium Chinese model.                                                      |
+----------------------------------------------------------------------------------+--------------+----------------------------------------------------------------------------------+
|``chinese-xlnet-large``                                                           | Chinese      | 24-layer, 1024-hidden,                                                           |
|                                                                                  |              | 16-heads, _M parameters.                                                         |
|                                                                                  |              | XLNet Large Chinese model.                                                       |
+----------------------------------------------------------------------------------+--------------+----------------------------------------------------------------------------------+