update readme

README.md

@@ -26,7 +26,7 @@ With Open-Sora, we aim to inspire innovation, creativity, and inclusivity in the
 * **[2024.03.18]** 🔥 We release **Open-Sora 1.0**, a fully open-source project for video generation.
 Open-Sora 1.0 supports a full pipeline of video data preprocessing, training with
 <a href="https://github.com/hpcaitech/ColossalAI"><img src="assets/readme/colossal_ai.png" width="8%" ></a> acceleration,
-inference, and more. Our provided [checkpoints](#model-weights) can produce 2~5s 512x512 videos with only 3 days training.
+inference, and more. Our provided [checkpoints](#model-weights) can produce 2s 512x512 videos with only 3 days training.
 * **[2024.03.04]** Open-Sora provides training with 46% cost reduction.
 
 ## 🎥 Latest Demo
@@ -123,7 +123,6 @@ After installation, we suggest reading [structure.md](docs/structure.md) to lear
 | 16×256×256 | 366K   | 80k         | 8×64       | 117             | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-16x256x256.pth)    |
 | 16×256×256 | 20K HQ | 24k         | 8×64       | 45              | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-HQ-16x256x256.pth) |
 | 16×512×512 | 20K HQ | 20k         | 2×64       | 35              | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-HQ-16x512x512.pth) |
-| 64×512×512 | 50K HQ |             |            |                 | TBD                                                                                           |
 
 Our model's weight is partially initialized from [PixArt-α](https://github.com/PixArt-alpha/PixArt-alpha). The number of parameters is 724M. More information about training can be found in our **[report](/docs/report_v1.md)**. More about dataset can be found in [dataset.md](/docs/dataset.md). HQ means high quality.
 

docs/README_zh.md

@@ -23,7 +23,7 @@
 
 * **[2024.03.18]** 🔥 我们发布了**Open-Sora 1.0**，这是一个完全开源的视频生成项目。
 * Open-Sora 1.0 支持视频数据预处理、<a href="https://github.com/hpcaitech/ColossalAI"><img src="../assets/readme/colossal_ai.png" width="8%" ></a> 加速训练、推理等全套流程。
-* 我们提供的[模型权重](#model-weights)只需 3 天的训练就能生成 2~5 秒的 512x512 视频。
+* 我们提供的[模型权重](#model-weights)只需 3 天的训练就能生成 2 秒的 512x512 视频。
 * **[2024.03.04]** Open-Sora：开源Sora复现方案，成本降低46%，序列扩充至近百万
 
 ## 🎥 最新视频
@@ -119,7 +119,6 @@ pip install -v .
 | 16×256×256 | 366K   | 80k         | 8×64       | 117             | [:link:]() |
 | 16×256×256 | 20K HQ | 24k         | 8×64       | 45              | [:link:]() |
 | 16×512×512 | 20K HQ | 20k         | 2×64       | 35              | [:link:]() |
-| 64×512×512 | 50K HQ |             |            |                 | TBD        |
 
 我们模型的权重部分由[PixArt-α](https://github.com/PixArt-alpha/PixArt-alpha) 初始化。参数数量为 724M。有关训练的更多信息，请参阅我们的 **[报告](/docs/report_v1.md)**。有关数据集的更多信息，请参阅[数据](/docs/dataset.md)。HQ 表示高质量。
 :warning: **局限性**：我们的模型是在有限的预算内训练出来的。质量和文本对齐度相对较差。特别是在生成人类时，模型表现很差，无法遵循详细的指令。我们正在努力改进质量和文本对齐。