# Prince Ciel Phantomhive HunyuanVideo LoRA This repository contains the necessary setup and scripts to generate videos using the HunyuanVideo model with a LoRA (Low-Rank Adaptation) fine-tuned for Ciel Phantomhive. Below are the instructions to install dependencies, download models, and run the demo. --- ## Installation ### Step 1: Install System Dependencies Run the following command to install required system packages: ```bash sudo apt-get update && sudo apt-get install git-lfs ffmpeg cbm ``` ### Step 2: Clone the Repository Clone the repository and navigate to the project directory: ```bash git clone https://huggingface.co/svjack/Prince_Ciel_Phantomhive_HunyuanVideo_lora cd Prince_Ciel_Phantomhive_HunyuanVideo_lora ``` ### Step 3: Install Python Dependencies Install the required Python packages: ```bash conda create -n py310 python=3.10 conda activate py310 pip install ipykernel python -m ipykernel install --user --name py310 --display-name "py310" pip install -r requirements.txt pip install ascii-magic matplotlib tensorboard huggingface_hub pip install moviepy==1.0.3 pip install sageattention==1.0.6 pip install torch==2.5.0 torchvision ``` --- ## Download Models ### Step 1: Download HunyuanVideo Model Download the HunyuanVideo model and place it in the `ckpts` directory: ```bash huggingface-cli download tencent/HunyuanVideo --local-dir ./ckpts ``` ### Step 2: Download LLaVA Model Download the LLaVA model and preprocess it: ```bash cd ckpts huggingface-cli download xtuner/llava-llama-3-8b-v1_1-transformers --local-dir ./llava-llama-3-8b-v1_1-transformers wget https://raw.githubusercontent.com/Tencent/HunyuanVideo/refs/heads/main/hyvideo/utils/preprocess_text_encoder_tokenizer_utils.py python preprocess_text_encoder_tokenizer_utils.py --input_dir llava-llama-3-8b-v1_1-transformers --output_dir text_encoder ``` ### Step 3: Download CLIP Model Download the CLIP model for the text encoder: ```bash huggingface-cli download openai/clip-vit-large-patch14 --local-dir ./text_encoder_2 ``` --- ## Demo ### Generate Video 1: Ciel Phantomhive Run the following command to generate a video of Ciel Phantomhive: ```bash python hv_generate_video.py \ --fp8 \ --video_size 544 960 \ --video_length 60 \ --infer_steps 30 \ --prompt "Ciel Phantomhive, depicted in a semi-realistic art style. Ciel has short, silver hair with bangs, and an eyepatch over his right eye. He wears a black military-style uniform with white accents, including a high-collared shirt and a belt with a buckle. His expression is stern and focused. The background is a soft, pastel purple, contrasting with the darker tones of his outfit. The image has a clean, polished look with smooth shading and attention to detail in the uniform's textures and folds." \ --save_path . \ --output_type both \ --dit ckpts/hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states.pt \ --attn_mode sdpa \ --vae ckpts/hunyuan-video-t2v-720p/vae/pytorch_model.pt \ --vae_chunk_size 32 \ --vae_spatial_tile_sample_min_size 128 \ --text_encoder1 ckpts/text_encoder \ --text_encoder2 ckpts/text_encoder_2 \ --seed 1234 \ --lora_multiplier 1.0 \ --lora_weight Ciel_im_lora_dir/Ciel_single_im_lora-000030.safetensors ``` ### Generate Video 2: Ciel Phantomhive Rain Run the following command to generate a video of Ciel Phantomhive in rain: ```bash python hv_generate_video.py \ --fp8 \ --video_size 544 960 \ --video_length 60 \ --infer_steps 30 \ --prompt "Ciel Phantomhive, depicted in a semi-realistic art style, stands amidst the bustling, rain-soaked streets of a city. Ciel has short, silver hair with bangs, and an eyepatch over his right eye. He wears a black military-style uniform with white accents, including a high-collared shirt and a belt with a buckle, the fabric slightly damp from the drizzle. His expression is stern and focused, as if undeterred by the chaotic surroundings. The background is a moody blend of gray skies and shimmering reflections from the wet pavement, with streaks of rain adding a dynamic texture. Neon lights from nearby buildings cast a faint glow, contrasting with the darker tones of his outfit. The image has a clean, polished look, with smooth shading and meticulous attention to detail in the uniform's textures and folds, emphasizing Ciel's commanding presence in the midst of the urban downpour." \ --save_path . \ --output_type both \ --dit ckpts/hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states.pt \ --attn_mode sdpa \ --vae ckpts/hunyuan-video-t2v-720p/vae/pytorch_model.pt \ --vae_chunk_size 32 \ --vae_spatial_tile_sample_min_size 128 \ --text_encoder1 ckpts/text_encoder \ --text_encoder2 ckpts/text_encoder_2 \ --seed 1234 \ --lora_multiplier 1.0 \ --lora_weight Ciel_im_lora_dir/Ciel_single_im_lora-000030.safetensors ``` --- ## Notes - Ensure you have sufficient GPU resources for video generation. - Adjust the `--video_size`, `--video_length`, and `--infer_steps` parameters as needed for different output qualities and lengths. - The `--prompt` parameter can be modified to generate videos with different scenes or actions. ---