Update Readme

README.md

@@ -86,8 +86,7 @@ EasyAnimateV5.1:
           <video src="https://github.com/user-attachments/assets/7f62795a-2b3b-4c14-aeb1-1230cb818067" width="100%" controls autoplay loop></video>
      </td>
       <td>
-          <video src="https://github.com/user-attachments/assets/b581df84-ade1-4605-a7a8-fd735ce3e222
-          " width="100%" controls autoplay loop></video>
+          <video src="https://github.com/user-attachments/assets/b581df84-ade1-4605-a7a8-fd735ce3e222" width="100%" controls autoplay loop></video>
      </td>
   </tr>
 </table>
@@ -360,6 +359,8 @@ EasyAnimateV5.1-7B的视频大小可以由不同的GPU Memory生成，包括：
 | 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

@@ -56,8 +56,7 @@ EasyAnimateV5.1:
           <video src="https://github.com/user-attachments/assets/7f62795a-2b3b-4c14-aeb1-1230cb818067" width="100%" controls autoplay loop></video>
      </td>
       <td>
-          <video src="https://github.com/user-attachments/assets/b581df84-ade1-4605-a7a8-fd735ce3e222
-          " width="100%" controls autoplay loop></video>
+          <video src="https://github.com/user-attachments/assets/b581df84-ade1-4605-a7a8-fd735ce3e222" width="100%" controls autoplay loop></video>
      </td>
   </tr>
 </table>
@@ -325,7 +324,7 @@ The video size for EasyAnimateV5.1-12B can be generated by different GPU Memory,
 | 40GB       | ✅         | ✅         | ✅         | ✅         | ❌         | ❌         |
 | 80GB       | ✅         | ✅         | ✅         | ✅         | ✅         | ✅         |
 
-The video size for EasyAnimateV5-7B can be generated by different GPU Memory, including:
+The video size for EasyAnimateV5.1-7B can be generated by different GPU Memory, including:
 | GPU memory | 384x672x72 | 384x672x49 | 576x1008x25 | 576x1008x49 | 768x1344x25 | 768x1344x49 |
 |------------|------------|------------|------------|------------|------------|------------|
 | 16GB       | 🧡         | 🧡         | ❌         | ❌         | ❌         | ❌         |
@@ -333,6 +332,7 @@ The video size for EasyAnimateV5-7B can be generated by different GPU Memory, in
 | 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).
 
 ✅ 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.