huggingface模型 推理

HuggingFace模型在推理方面具有很高的效率和准确性。根据引用，HuggingFace模型在语义相似度数据集LCQMC测试集上的准确率达到了85.4%，相比于BERT_base只下降了1.5个百分点。此外，根据引用的信息，使用HuggingFace-transformers系列的模型进行训练和推理预测可以显著提高速度，约为原本的10倍，并且模型大小只有BERT的1/25。这意味着HuggingFace模型可以在保持精度的同时，极大地提升推理的效率。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *2* [HuggingFace模型训练以及推理相关](https://blog.csdn.net/weixin_41912999/article/details/129922902)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
- *3* [中文预训练ALBERT模型.zip](https://download.csdn.net/download/baidu_38876334/87975282)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
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