From 44539fe77bd095cb3dbc5b12cf27fa15c548c3fd Mon Sep 17 00:00:00 2001 From: Bubbliiiing <47347516+bubbliiiing@users.noreply.github.com> Date: Fri, 8 Nov 2024 22:38:17 +0800 Subject: [PATCH] Update Readme (#130) --- README.md | 2 +- README_zh-CN.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 089110f..91b2d90 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,7 @@ EasyAnimate is a pipeline based on the transformer architecture, designed for ge We will support quick pull-ups from different platforms, refer to [Quick Start](#quick-start). **New Features:** -- **Updated to v5**, supporting video generation up to 1024x1024, 49 frames, 6s, 8fps, with expanded model scale to 12B, incorporating the MMDIT structure, and enabling control models with diverse inputs; supports bilingual predictions in Chinese and English. [2024.11.04] +- **Updated to v5**, supporting video generation up to 1024x1024, 49 frames, 6s, 8fps, with expanded model scale to 12B, incorporating the MMDIT structure, and enabling control models with diverse inputs; supports bilingual predictions in Chinese and English. [2024.11.08] - **Updated to v4**, allowing for video generation up to 1024x1024, 144 frames, 6s, 24fps; supports video generation from text, image, and video, with a single model handling resolutions from 512 to 1280; bilingual predictions in Chinese and English enabled. [2024.08.15] - **Updated to v3**, supporting video generation up to 960x960, 144 frames, 6s, 24fps, from text and image. [2024.07.01] - **ModelScope-Sora “Data Director” Creative Race** — The third Data-Juicer Big Model Data Challenge is now officially launched! Utilizing EasyAnimate as the base model, it explores the impact of data processing on model training. Visit the [competition website](https://tianchi.aliyun.com/competition/entrance/532219) for details. [2024.06.17] diff --git a/README_zh-CN.md b/README_zh-CN.md index 9e032d1..2d82f84 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -31,7 +31,7 @@ EasyAnimate是一个基于transformer结构的pipeline，可用于生成AI图片 我们会逐渐支持从不同平台快速启动，请参阅 [快速启动](#快速启动)。 新特性： -- 更新到v5版本，最大支持1024x1024，49帧, 6s, 8fps视频生成，拓展模型规模到12B，应用MMDIT结构，支持不同输入的控制模型，支持中文与英文双语预测。[ 2024.11.04 ] +- 更新到v5版本，最大支持1024x1024，49帧, 6s, 8fps视频生成，拓展模型规模到12B，应用MMDIT结构，支持不同输入的控制模型，支持中文与英文双语预测。[ 2024.11.08 ] - 更新到v4版本，最大支持1024x1024，144帧, 6s, 24fps视频生成，支持文、图、视频生视频，单个模型可支持512到1280任意分辨率，支持中文与英文双语预测。[ 2024.08.15 ] - 更新到v3版本，最大支持960x960，144帧，6s, 24fps视频生成，支持文与图生视频模型。[ 2024.07.01 ] - ModelScope-Sora“数据导演”创意竞速——第三届Data-Juicer大模型数据挑战赛已经正式启动！其使用EasyAnimate作为基础模型，探究数据处理对于模型训练的作用。立即访问[竞赛官网](https://tianchi.aliyun.com/competition/entrance/532219)，了解赛事详情。[ 2024.06.17 ]