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docs/source_en/finetune/train_hunyuan_dit_lora.md

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+# Training Hunyuan-DiT LoRA
+
+Building the Hunyuan DiT model requires four files. You can download these files from [HuggingFace](https://huggingface.co/Tencent-Hunyuan/HunyuanDiT) or [ModelScope](https://www.modelscope.cn/models/modelscope/HunyuanDiT/summary). You can use the following code to download these files:
+
+```python
+from diffsynth import download_models
+
+download_models(["HunyuanDiT"])
+```
+
+```
+models/HunyuanDiT/
+├── Put Hunyuan DiT checkpoints here.txt
+└── t2i
+    ├── clip_text_encoder
+    │   └── pytorch_model.bin
+    ├── model
+    │   └── pytorch_model_ema.pt
+    ├── mt5
+    │   └── pytorch_model.bin
+    └── sdxl-vae-fp16-fix
+        └── diffusion_pytorch_model.bin
+```
+
+Use the following command to start the training task:
+
+```
+CUDA_VISIBLE_DEVICES="0" python examples/train/hunyuan_dit/train_hunyuan_dit_lora.py \
+  --pretrained_path models/HunyuanDiT/t2i \
+  --dataset_path data/dog \
+  --output_path ./models \
+  --max_epochs 1 \
+  --steps_per_epoch 500 \
+  --height 1024 \
+  --width 1024 \
+  --center_crop \
+  --precision "16-mixed" \
+  --learning_rate 1e-4 \
+  --lora_rank 4 \
+  --lora_alpha 4 \
+  --use_gradient_checkpointing
+```
+
+For more information about the parameters, please use `python examples/train/hunyuan_dit/train_hunyuan_dit_lora.py -h` to view detailed information.
+
+After the training is complete, use `model_manager.load_lora` to load the LoRA for inference.
+
+
+```python
+from diffsynth import ModelManager, HunyuanDiTImagePipeline
+import torch
+
+model_manager = ModelManager(torch_dtype=torch.float16, device="cuda",
+                             file_path_list=[
+                                 "models/HunyuanDiT/t2i/clip_text_encoder/pytorch_model.bin",
+                                 "models/HunyuanDiT/t2i/model/pytorch_model_ema.pt",
+                                 "models/HunyuanDiT/t2i/mt5/pytorch_model.bin",
+                                 "models/HunyuanDiT/t2i/sdxl-vae-fp16-fix/diffusion_pytorch_model.bin"
+                             ])
+model_manager.load_lora("models/lightning_logs/version_0/checkpoints/epoch=0-step=500.ckpt", lora_alpha=1.0)
+pipe = HunyuanDiTImagePipeline.from_model_manager(model_manager)
+
+torch.manual_seed(0)
+image = pipe(
+    prompt="A little puppy hops and jumps playfully, surrounded by a profusion of colorful flowers, with a mountain range visible in the distance.
+", 
+    negative_prompt="",
+    cfg_scale=7.5,
+    num_inference_steps=100, width=1024, height=1024,
+)
+image.save("image_with_lora.jpg")
+```