From 09146fc0a54c98d3f87335ea48ffc1533f0a8775 Mon Sep 17 00:00:00 2001
From: "wenmeng.zwm" <wenmeng.zwm@alibaba-inc.com>
Date: Fri, 17 Feb 2023 11:25:24 +0800
Subject: [PATCH] update readme

---
 README.md    | 66 +++++++++++++++++++++++++++-------------------------
 README_zh.md | 65 ++++++++++++++++++++++++++-------------------------
 2 files changed, 67 insertions(+), 64 deletions(-)

diff --git a/README.md b/README.md
index 0993fc39..6bd4c732 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
 
 <p align="center">
     <br>
-    <img src="https://modelscope.oss-cn-beijing.aliyuncs.com/logo.png" width="400"/>
+    <img src="https://modelscope.oss-cn-beijing.aliyuncs.com/modelscope.gif" width="400"/>
     <br>
 <p>
 
@@ -43,71 +43,71 @@ Here are some examples:
 
 NLP:
 
-[nlp_gpt3_text-generation_2.7B](https://modelscope.cn/models/damo/nlp_gpt3_text-generation_2.7B)
+* [nlp_gpt3_text-generation_2.7B](https://modelscope.cn/models/damo/nlp_gpt3_text-generation_2.7B)
 
-[ChatYuan-large](https://modelscope.cn/models/ClueAI/ChatYuan-large)
+* [ChatYuan-large](https://modelscope.cn/models/ClueAI/ChatYuan-large)
 
-[mengzi-t5-base](https://modelscope.cn/models/langboat/mengzi-t5-base)
+* [mengzi-t5-base](https://modelscope.cn/models/langboat/mengzi-t5-base)
 
-[nlp_csanmt_translation_en2zh](https://modelscope.cn/models/damo/nlp_csanmt_translation_en2zh)
+* [nlp_csanmt_translation_en2zh](https://modelscope.cn/models/damo/nlp_csanmt_translation_en2zh)
 
-[nlp_raner_named-entity-recognition_chinese-base-news](https://modelscope.cn/models/damo/nlp_raner_named-entity-recognition_chinese-base-news)
+* [nlp_raner_named-entity-recognition_chinese-base-news](https://modelscope.cn/models/damo/nlp_raner_named-entity-recognition_chinese-base-news)
 
-[nlp_structbert_word-segmentation_chinese-base](https://modelscope.cn/models/damo/nlp_structbert_word-segmentation_chinese-base)
+* * [nlp_structbert_word-segmentation_chinese-base](https://modelscope.cn/models/damo/nlp_structbert_word-segmentation_chinese-base)
 
-[Erlangshen-RoBERTa-330M-Sentiment](https://modelscope.cn/models/fengshenbang/Erlangshen-RoBERTa-330M-Sentiment)
+* [Erlangshen-RoBERTa-330M-Sentiment](https://modelscope.cn/models/fengshenbang/Erlangshen-RoBERTa-330M-Sentiment)
 
-[nlp_convai_text2sql_pretrain_cn](https://modelscope.cn/models/damo/nlp_convai_text2sql_pretrain_cn)
+* [nlp_convai_text2sql_pretrain_cn](https://modelscope.cn/models/damo/nlp_convai_text2sql_pretrain_cn)
 
 Audio:
 
-[speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch)
+* [speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch)
 
-[speech_sambert-hifigan_tts_zh-cn_16k](https://modelscope.cn/models/damo/speech_sambert-hifigan_tts_zh-cn_16k)
+* [speech_sambert-hifigan_tts_zh-cn_16k](https://modelscope.cn/models/damo/speech_sambert-hifigan_tts_zh-cn_16k)
 
-[speech_charctc_kws_phone-xiaoyun](https://modelscope.cn/models/damo/speech_charctc_kws_phone-xiaoyun)
+* [speech_charctc_kws_phone-xiaoyun](https://modelscope.cn/models/damo/speech_charctc_kws_phone-xiaoyun)
 
-[u2pp_conformer-asr-cn-16k-online](https://modelscope.cn/models/wenet/u2pp_conformer-asr-cn-16k-online)
+* [u2pp_conformer-asr-cn-16k-online](https://modelscope.cn/models/wenet/u2pp_conformer-asr-cn-16k-online)
 
-[speech_frcrn_ans_cirm_16k](https://modelscope.cn/models/damo/speech_frcrn_ans_cirm_16k)
+* [speech_frcrn_ans_cirm_16k](https://modelscope.cn/models/damo/speech_frcrn_ans_cirm_16k)
 
-[speech_dfsmn_aec_psm_16k](https://modelscope.cn/models/damo/speech_dfsmn_aec_psm_16k)
+* [speech_dfsmn_aec_psm_16k](https://modelscope.cn/models/damo/speech_dfsmn_aec_psm_16k)
 
 
 CV:
 
-[cv_tinynas_object-detection_damoyolo](https://modelscope.cn/models/damo/cv_tinynas_object-detection_damoyolo)
+* [cv_tinynas_object-detection_damoyolo](https://modelscope.cn/models/damo/cv_tinynas_object-detection_damoyolo)
 
-[cv_unet_person-image-cartoon_compound-models](https://modelscope.cn/models/damo/cv_unet_person-image-cartoon_compound-models)
+* [cv_unet_person-image-cartoon_compound-models](https://modelscope.cn/models/damo/cv_unet_person-image-cartoon_compound-models)
 
-[cv_convnextTiny_ocr-recognition-general_damo](https://modelscope.cn/models/damo/cv_convnextTiny_ocr-recognition-general_damo)
+* [cv_convnextTiny_ocr-recognition-general_damo](https://modelscope.cn/models/damo/cv_convnextTiny_ocr-recognition-general_damo)
 
-[cv_resnet18_human-detection](https://modelscope.cn/models/damo/cv_resnet18_human-detection)
+* [cv_resnet18_human-detection](https://modelscope.cn/models/damo/cv_resnet18_human-detection)
 
-[cv_resnet50_face-detection_retinaface](https://modelscope.cn/models/damo/cv_resnet50_face-detection_retinaface)
+* [cv_resnet50_face-detection_retinaface](https://modelscope.cn/models/damo/cv_resnet50_face-detection_retinaface)
 
-[cv_unet_image-matting](https://modelscope.cn/models/damo/cv_unet_image-matting)
+* [cv_unet_image-matting](https://modelscope.cn/models/damo/cv_unet_image-matting)
 
-[cv_F3Net_product-segmentation](https://modelscope.cn/models/damo/cv_F3Net_product-segmentation)
+* [cv_F3Net_product-segmentation](https://modelscope.cn/models/damo/cv_F3Net_product-segmentation)
 
-[cv_resnest101_general_recognition](https://modelscope.cn/models/damo/cv_resnest101_general_recognition)
+* [cv_resnest101_general_recognition](https://modelscope.cn/models/damo/cv_resnest101_general_recognition)
 
 
 Multi-Modal:
 
-[multi-modal_clip-vit-base-patch16_zh](https://modelscope.cn/models/damo/multi-modal_clip-vit-base-patch16_zh)
+* [multi-modal_clip-vit-base-patch16_zh](https://modelscope.cn/models/damo/multi-modal_clip-vit-base-patch16_zh)
 
-[ofa_pretrain_base_zh](https://modelscope.cn/models/damo/ofa_pretrain_base_zh)
+* [ofa_pretrain_base_zh](https://modelscope.cn/models/damo/ofa_pretrain_base_zh)
 
-[Taiyi-Stable-Diffusion-1B-Chinese-v0.1](https://modelscope.cn/models/fengshenbang/Taiyi-Stable-Diffusion-1B-Chinese-v0.1)
+* [Taiyi-Stable-Diffusion-1B-Chinese-v0.1](https://modelscope.cn/models/fengshenbang/Taiyi-Stable-Diffusion-1B-Chinese-v0.1)
 
-[mplug_visual-question-answering_coco_large_en](https://modelscope.cn/models/damo/mplug_visual-question-answering_coco_large_en)
+* [mplug_visual-question-answering_coco_large_en](https://modelscope.cn/models/damo/mplug_visual-question-answering_coco_large_en)
 
 AI for Science:
 
-[uni-fold-monomer](https://modelscope.cn/models/DPTech/uni-fold-monomer/summary)
+* [uni-fold-monomer](https://modelscope.cn/models/DPTech/uni-fold-monomer/summary)
 
-[uni-fold-multimer](https://modelscope.cn/models/DPTech/uni-fold-multimer/summary)
+* [uni-fold-multimer](https://modelscope.cn/models/DPTech/uni-fold-multimer/summary)
 
 # QuickTour
 
@@ -162,11 +162,13 @@ For finetuning and evaluation, you need ten more lines of code to construct data
 
 # Why should I use ModelScope library
 
-1. ModelScope library provides a unified way for model inference, training, and evaluation, which is simple to use.
+1. A unified and concise user interface is abstracted for different tasks and different models. Three lines of code complete the inference, and 10 lines of code complete the model training. It is convenient for users to use different models in multiple fields in the ModelScope community. It is ready to use and easy to get started with AI. and teaching.
 
-2. ModelScope library provides interfaces and implementations for different models to access the ModelScope ecosystem. It is compatible with various machine learning frameworks and seamlessly connects model application and development.
+2. Construct a model-centric development and application experience, support model training, inference, export and deployment, and facilitate users to build their own MLOps based on the ModelScope Library.
 
-3. There are more than 600 models in ModelScope community, covering CV, speech, NLP, multi-modality and AI for Science, covering more than 60 tasks. It contains nearly a hundred SOTA (industry-leading) models and more than a dozen pre-trained large models, all of which have been open source or open for use.
+3. For the model inference and training process, a modular design is carried out, and a wealth of functional module implementations are provided, which is convenient for users to customize development to customize their own model inference, training and other processes.
+
+4. For distributed model training, especially for large models, it provides rich training strategy support.
 
 # Installation
 ModelScope Library currently supports tensorflow and pytorch deep learning framework for model training and inference, and it is tested and run on Python 3.7+, Pytorch 1.8+, Tensorflow1.15 or Tensorflow2.0+.
diff --git a/README_zh.md b/README_zh.md
index 042f9aed..9d1a1efd 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -1,7 +1,7 @@
 
 <p align="center">
     <br>
-    <img src="https://modelscope.oss-cn-beijing.aliyuncs.com/logo.png" width="400"/>
+    <img src="https://modelscope.oss-cn-beijing.aliyuncs.com/modelscope.gif" width="400"/>
     <br>
 <p>
 
@@ -43,71 +43,71 @@ ModelScope开源了600多个模型，涵盖NLP、CV、Audio、多模态、科学
 
 自然语言处理：
 
-[GPT-3预训练生成模型-中文-2.7B](https://modelscope.cn/models/damo/nlp_gpt3_text-generation_2.7B)
+* [GPT-3预训练生成模型-中文-2.7B](https://modelscope.cn/models/damo/nlp_gpt3_text-generation_2.7B)
 
-[元语功能型对话大模型](https://modelscope.cn/models/ClueAI/ChatYuan-large)
+* [元语功能型对话大模型](https://modelscope.cn/models/ClueAI/ChatYuan-large)
 
-[孟子T5预训练生成模型-中文-base](https://modelscope.cn/models/langboat/mengzi-t5-base)
+* [孟子T5预训练生成模型-中文-base](https://modelscope.cn/models/langboat/mengzi-t5-base)
 
-[CSANMT连续语义增强机器翻译-英中-通用领域-large](https://modelscope.cn/models/damo/nlp_csanmt_translation_en2zh)
+* [CSANMT连续语义增强机器翻译-英中-通用领域-large](https://modelscope.cn/models/damo/nlp_csanmt_translation_en2zh)
 
-[RaNER命名实体识别-中文-新闻领域-base](https://modelscope.cn/models/damo/nlp_raner_named-entity-recognition_chinese-base-news)
+* [RaNER命名实体识别-中文-新闻领域-base](https://modelscope.cn/models/damo/nlp_raner_named-entity-recognition_chinese-base-news)
 
-[BAStructBERT分词-中文-新闻领域-base](https://modelscope.cn/models/damo/nlp_structbert_word-segmentation_chinese-base)
+* [BAStructBERT分词-中文-新闻领域-base](https://modelscope.cn/models/damo/nlp_structbert_word-segmentation_chinese-base)
 
-[二郎神-RoBERTa-330M-情感分类](https://modelscope.cn/models/fengshenbang/Erlangshen-RoBERTa-330M-Sentiment)
+* [二郎神-RoBERTa-330M-情感分类](https://modelscope.cn/models/fengshenbang/Erlangshen-RoBERTa-330M-Sentiment)
 
-[SPACE-T表格问答预训练模型-中文-通用领域-base](https://modelscope.cn/models/damo/nlp_convai_text2sql_pretrain_cn)
+* [SPACE-T表格问答预训练模型-中文-通用领域-base](https://modelscope.cn/models/damo/nlp_convai_text2sql_pretrain_cn)
 
 语音：
 
-[Paraformer语音识别-中文-通用-16k-离线-large-pytorch](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch)
+* [Paraformer语音识别-中文-通用-16k-离线-large-pytorch](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch)
 
-[语音合成-中文-多情感领域-16k-多发音人](https://modelscope.cn/models/damo/speech_sambert-hifigan_tts_zh-cn_16k)
+* [语音合成-中文-多情感领域-16k-多发音人](https://modelscope.cn/models/damo/speech_sambert-hifigan_tts_zh-cn_16k)
 
-[CTC语音唤醒-移动端-单麦-16k-小云小云](https://modelscope.cn/models/damo/speech_charctc_kws_phone-xiaoyun)
+* [CTC语音唤醒-移动端-单麦-16k-小云小云](https://modelscope.cn/models/damo/speech_charctc_kws_phone-xiaoyun)
 
-[WeNet-U2pp_Conformer-语音识别-中文-16k-实时](https://modelscope.cn/models/wenet/u2pp_conformer-asr-cn-16k-online)
+* [WeNet-U2pp_Conformer-语音识别-中文-16k-实时](https://modelscope.cn/models/wenet/u2pp_conformer-asr-cn-16k-online)
 
-[FRCRN语音降噪-单麦-16k](https://modelscope.cn/models/damo/speech_frcrn_ans_cirm_16k)
+* [FRCRN语音降噪-单麦-16k](https://modelscope.cn/models/damo/speech_frcrn_ans_cirm_16k)
 
-[DFSMN回声消除-单麦单参考-16k](https://modelscope.cn/models/damo/speech_dfsmn_aec_psm_16k)
+* [DFSMN回声消除-单麦单参考-16k](https://modelscope.cn/models/damo/speech_dfsmn_aec_psm_16k)
 
 
 计算机视觉：
 
-[DAMOYOLO-高性能通用检测模型-S](https://modelscope.cn/models/damo/cv_tinynas_object-detection_damoyolo)
+* [DAMOYOLO-高性能通用检测模型-S](https://modelscope.cn/models/damo/cv_tinynas_object-detection_damoyolo)
 
-[DCT-Net人像卡通化](https://modelscope.cn/models/damo/cv_unet_person-image-cartoon_compound-models)
+* [DCT-Net人像卡通化](https://modelscope.cn/models/damo/cv_unet_person-image-cartoon_compound-models)
 
-[读光-文字识别-行识别模型-中英-通用领域](https://modelscope.cn/models/damo/cv_convnextTiny_ocr-recognition-general_damo)
+* [读光-文字识别-行识别模型-中英-通用领域](https://modelscope.cn/models/damo/cv_convnextTiny_ocr-recognition-general_damo)
 
-[人体检测-通用-Base](https://modelscope.cn/models/damo/cv_resnet18_human-detection)
+* [人体检测-通用-Base](https://modelscope.cn/models/damo/cv_resnet18_human-detection)
 
-[RetinaFace人脸检测关键点模型](https://modelscope.cn/models/damo/cv_resnet50_face-detection_retinaface)
+* [RetinaFace人脸检测关键点模型](https://modelscope.cn/models/damo/cv_resnet50_face-detection_retinaface)
 
-[BSHM人像抠图](https://modelscope.cn/models/damo/cv_unet_image-matting)
+* [BSHM人像抠图](https://modelscope.cn/models/damo/cv_unet_image-matting)
 
-[图像分割-商品展示图场景的商品分割-电商领域](https://modelscope.cn/models/damo/cv_F3Net_product-segmentation)
+* [图像分割-商品展示图场景的商品分割-电商领域](https://modelscope.cn/models/damo/cv_F3Net_product-segmentation)
 
-[万物识别-中文-通用领域](https://modelscope.cn/models/damo/cv_resnest101_general_recognition)
+* [万物识别-中文-通用领域](https://modelscope.cn/models/damo/cv_resnest101_general_recognition)
 
 
 多模态：
 
-[CLIP模型-中文-通用领域-base](https://modelscope.cn/models/damo/multi-modal_clip-vit-base-patch16_zh)
+* [CLIP模型-中文-通用领域-base](https://modelscope.cn/models/damo/multi-modal_clip-vit-base-patch16_zh)
 
-[OFA预训练模型-中文-通用领域-base](https://modelscope.cn/models/damo/ofa_pretrain_base_zh)
+* [OFA预训练模型-中文-通用领域-base](https://modelscope.cn/models/damo/ofa_pretrain_base_zh)
 
-[太乙-Stable-Diffusion-1B-中文-v0.1](https://modelscope.cn/models/fengshenbang/Taiyi-Stable-Diffusion-1B-Chinese-v0.1)
+* [太乙-Stable-Diffusion-1B-中文-v0.1](https://modelscope.cn/models/fengshenbang/Taiyi-Stable-Diffusion-1B-Chinese-v0.1)
 
-[mPLUG视觉问答模型-英文-large](https://modelscope.cn/models/damo/mplug_visual-question-answering_coco_large_en)
+* [mPLUG视觉问答模型-英文-large](https://modelscope.cn/models/damo/mplug_visual-question-answering_coco_large_en)
 
 科学计算：
 
-[Uni-Fold-Monomer 开源的蛋白质单体结构预测模型](https://modelscope.cn/models/DPTech/uni-fold-monomer/summary)
+* [Uni-Fold-Monomer 开源的蛋白质单体结构预测模型](https://modelscope.cn/models/DPTech/uni-fold-monomer/summary)
 
-[Uni-Fold-Multimer 开源的蛋白质复合物结构预测模型](https://modelscope.cn/models/DPTech/uni-fold-multimer/summary)
+* [Uni-Fold-Multimer 开源的蛋白质复合物结构预测模型](https://modelscope.cn/models/DPTech/uni-fold-multimer/summary)
 
 # 快速上手
 
@@ -161,12 +161,13 @@ ModelScope开源了600多个模型，涵盖NLP、CV、Audio、多模态、科学
 
 # 为什么要用ModelScope library
 
-1. 魔搭ModelScope Library针对模型推理、训练、评估提供了统一的接口，开箱即用。
+1. 针对不同任务、不同模型抽象了统一简洁的用户接口，3行代码完成推理，10行代码完成模型训练，方便用户使用ModelScope社区中多个领域的不同模型，开箱即用，便于AI入门和教学。
 
-2. 魔搭ModelScope Library提供了不同模型接入ModelScope生态的接口和实现，底层能够兼容各种机器学习框架，无缝衔接模型应用与开发。
+2. 构造以模型为中心的开发应用体验，支持模型训练、推理、导出部署，方便用户基于ModelScope Library构建自己的MLOps.
 
-3. 魔搭ModelScope社区上架模型超过600个，覆盖了视觉、语音、自然语言处理、多模态等AI主要领域，覆盖任务超过60个。其中包含近百个SOTA（业界领先）模型和十多个预训练大模型，均已开源代码或开放使用。 。
+3. 针对模型推理、训练流程，进行了模块化的设计，并提供了丰富的功能模块实现，方便用户定制化开发来自定义自己的推理、训练等过程。
 
+4. 针对分布式模型训练，尤其是大模型，提供了丰富的训练策略支持。
 
 # 安装
 ModelScope Library目前支持tensorflow，pytorch深度学习框架进行模型训练、推理， 在Python 3.7+, Pytorch 1.8+, Tensorflow1.15/Tensorflow2.0+测试可运行。