【1、模型部分能力升级】
- 新模型支持：新增轻量级中文对话模型plato-mini，新增基于VOC数据集的高精度语义分割模型2个，语音分类模型3个。
- 迁移学习能力升级：新增图像语义分割、文本语义匹配、语音分类等相关任务的Fine-Tune能力以及相关任务数据集。
【2、部署能力重要升级】
- 完善部署能力：新增ONNX和PaddleInference等模型格式的导出功能。
- 重要开源生态合作：新增BentoML 云原生服务化部署能力，可以支持统一的多框架模型管理和模型部署的工作流，详细教程.
更多内容可以参考BentoML 最新 v0.12.1 Releasenote
（感谢@ parano @cqvu @deehrlic）的贡献与支持
【3、问题修复】
[ 1. Improvements]
- Add supports for six new models, including an open-domain dialogue system(plato-mini), two high-precision semantic segmentation models based on VOC dataset and three voice classification models.
- Enforce the transfer learning capabilities for image semantic segmentation, text semantic matching and voice classification on related datasets.
[ 2. Upgrades of deployment capabilities]
- Add the export function APIs for two kinds of model formats, i.,e, ONNX and PaddleInference.
- Important Open-Source Ecological Cooperation: add the support for BentoML, which is a cloud native framework for serving deployment. Users can easily serve pre-trained models from PaddleHub by following the [Tutorial notebooks](https:// github.com/PaddlePaddle/PaddleHub/tree/release/v2.1/demo/serving/BentoML). Also, see this announcement and Release note from BentoML. (Many thanks to @parano @cqvu @deehrlic for contributing this feature in PaddleHub)