Update Readme

README.md

@@ -324,23 +324,21 @@ Linux 的详细信息：
 我们需要大约 60GB 的可用磁盘空间，请检查！
 
 EasyAnimateV5.1-12B的视频大小可以由不同的GPU Memory生成，包括：
-| GPU memory |384x672x72|384x672x49|576x1008x25|576x1008x49|768x1344x25|768x1344x49|
+| GPU memory |384x672x25|384x672x49|576x1008x25|576x1008x49|768x1344x25|768x1344x49|
 |----------|----------|----------|----------|----------|----------|----------|
-| 16GB | 🧡 | 🧡 | ❌ | ❌ | ❌ | ❌ | 
-| 24GB | 🧡 | 🧡 | 🧡 | 🧡 | ❌ | ❌ | 
-| 40GB | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | 
+| 16GB | 🧡 | ⭕️ | ⭕️ | ⭕️ | ❌ | ❌ | 
+| 24GB | 🧡 | 🧡 | 🧡 | 🧡 | 🧡 | ❌ | 
+| 40GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
 | 80GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
 
 EasyAnimateV5.1-7B的视频大小可以由不同的GPU Memory生成，包括：
-| GPU memory |384x672x72|384x672x49|576x1008x25|576x1008x49|768x1344x25|768x1344x49|
+| GPU memory |384x672x25|384x672x49|576x1008x25|576x1008x49|768x1344x25|768x1344x49|
 |----------|----------|----------|----------|----------|----------|----------|
-| 16GB | 🧡 | 🧡 | ❌ | ❌ | ❌ | ❌ | 
-| 24GB | ✅ | ✅ | 🧡 | 🧡 | ❌ | ❌ | 
-| 40GB | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | 
+| 16GB | 🧡 | 🧡 | ⭕️ | ⭕️ | ❌ | ❌ | 
+| 24GB | ✅ | ✅ | ✅ | 🧡 | 🧡 | ❌ | 
+| 40GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
 | 80GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
 
-由于qwen2-vl-7b的float16的权重，无法在16GB显存下运行，如果您的显存是16GB，请前往[Huggingface](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8)或者[Modelscope](https://modelscope.cn/models/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8)下载量化后的qwen2-vl-7b对原有的text encoder进行替换，并安装对应的依赖库（auto-gptq, optimum）。
-
 ✅ 表示它可以在"model_cpu_offload"的情况下运行，🧡代表它可以在"model_cpu_offload_and_qfloat8"的情况下运行，⭕️ 表示它可以在"sequential_cpu_offload"的情况下运行，❌ 表示它无法运行。请注意，使用sequential_cpu_offload运行会更慢。
 
 有一些不支持torch.bfloat16的卡型，如2080ti、V100，需要将app.py、predict文件中的weight_dtype修改为torch.float16才可以运行。

README_en.md

@@ -325,22 +325,20 @@ The detailed of Linux:
 We need about 60GB available on disk (for saving weights), please check!
 
 The video size for EasyAnimateV5.1-12B can be generated by different GPU Memory, including:
-| GPU memory | 384x672x72 | 384x672x49 | 576x1008x25 | 576x1008x49 | 768x1344x25 | 768x1344x49 |
+| GPU memory | 384x672x25 | 384x672x49 | 576x1008x25 | 576x1008x49 | 768x1344x25 | 768x1344x49 |
 |------------|------------|------------|------------|------------|------------|------------|
-| 16GB       | 🧡         | 🧡         | ❌         | ❌         | ❌         | ❌         |
-| 24GB       | 🧡         | 🧡         | 🧡         | 🧡         | ❌         | ❌         |
-| 40GB       | ✅         | ✅         | ✅         | ✅         | ❌         | ❌         |
-| 80GB       | ✅         | ✅         | ✅         | ✅         | ✅         | ✅         |
+| 16GB | 🧡 | ⭕️ | ⭕️ | ⭕️ | ❌ | ❌ |
+| 24GB | 🧡 | 🧡 | 🧡 | 🧡 | 🧡 | ❌ | 
+| 40GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
+| 80GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
 
 The video size for EasyAnimateV5.1-7B can be generated by different GPU Memory, including:
-| GPU memory | 384x672x72 | 384x672x49 | 576x1008x25 | 576x1008x49 | 768x1344x25 | 768x1344x49 |
-|------------|------------|------------|------------|------------|------------|------------|
-| 16GB       | 🧡         | 🧡         | ❌         | ❌         | ❌         | ❌         |
-| 24GB       | ✅         | ✅         | 🧡         | 🧡         | ❌         | ❌         |
-| 40GB       | ✅         | ✅         | ✅         | ✅         | ❌         | ❌         |
-| 80GB       | ✅         | ✅         | ✅         | ✅         | ✅         | ✅         |
-
-Due to the float16 weights of qwen2-vl-7b, it cannot run on a 16GB GPU. If your GPU memory is 16GB, please visit [Huggingface](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8) or [Modelscope](https://modelscope.cn/models/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8) to download the quantized version of qwen2-vl-7b to replace the original text encoder, and install the corresponding dependency libraries (auto-gptq, optimum).
+| GPU memory |384x672x25|384x672x49|576x1008x25|576x1008x49|768x1344x25|768x1344x49|
+|----------|----------|----------|----------|----------|----------|----------|
+| 16GB | 🧡 | 🧡 | ⭕️ | ⭕️ | ❌ | ❌ | 
+| 24GB | ✅ | ✅ | ✅ | 🧡 | 🧡 | ❌ | 
+| 40GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
+| 80GB | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 
 
 ✅ indicates it can run under "model_cpu_offload", 🧡 represents it can run under "model_cpu_offload_and_qfloat8", ⭕️ indicates it can run under "sequential_cpu_offload", ❌ means it can't run. Please note that running with sequential_cpu_offload will be slower.