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README.md

@@ -1,19 +1,19 @@
 ---
 license: apache-2.0
 ---
-# Templates-魔性熊猫（FLUX.2-klein-base-4B）
+# Templates-PandaMeme (FLUX.2-klein-base-4B)
 
-本模型是 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) 开源的首批 Diffusion Templates 系列模型。这是一个彩蛋模型，能够生成各种魔性的熊猫头表情包。
+This model is part of the first batch of Diffusion Templates series models open-sourced by [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio). It's an Easter egg model capable of generating various quirky panda-head meme images.
 
-## 效果展示
+## Demo
 
 |Prompt: A meme with a happy expression.|Prompt: A meme with a sleepy expression.|Prompt: A meme with a surprised expression.|
 |-|-|-|
 |![](./assets/image_PandaMeme_happy.jpg)|![](./assets/image_PandaMeme_sleepy.jpg)|![](./assets/image_PandaMeme_surprised.jpg)|
 
-## 推理代码
+## Inference Code
 
-* 安装 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
+* Install [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
 
 ```
 git clone https://github.com/modelscope/DiffSynth-Studio.git
@@ -21,12 +21,13 @@ cd DiffSynth-Studio
 pip install -e .
 ```
 
-* 直接推理，需 40G 显存
+* Direct inference (requires 40G GPU memory)
 
 ```python
 from diffsynth.diffusion.template import TemplatePipeline
 from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
 import torch
+```
 
 pipe = Flux2ImagePipeline.from_pretrained(
     torch_dtype=torch.bfloat16,
@@ -69,13 +70,14 @@ image = template(
 image.save("image_PandaMeme_surprised.jpg")
 ```
 
-* 开启惰性加载和显存管理，需 24G 显存
+* Enable lazy loading and memory management, requires 24G GPU memory
 
 ```python
 from diffsynth.diffusion.template import TemplatePipeline
 from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
 import torch
 
+```python
 vram_config = {
     "offload_dtype": "disk",
     "offload_device": "disk",
@@ -129,9 +131,9 @@ image = template(
 image.save("image_PandaMeme_surprised.jpg")
 ```
 
-## 训练代码
+## Training Code
 
-安装 DiffSynth-Studio 后，使用以下脚本可开启训练，更多信息请参考 [DiffSynth-Studio 文档](https://diffsynth-studio-doc.readthedocs.io/zh-cn/latest/)。
+After installing DiffSynth-Studio, use the following script to start training. For more information, please refer to the [DiffSynth-Studio Documentation](https://diffsynth-studio-doc.readthedocs.io/zh-cn/latest/).
 
 ```shell
 modelscope download --dataset DiffSynth-Studio/diffsynth_example_dataset --include "flux2/Template-KleinBase4B-PandaMeme/*" --local_dir ./data/diffsynth_example_dataset