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svjack/
Xiang_Handsome_wan_2_1_1_3_B_text2video_lora

Name: Xiang_Handsome_wan_2_1_1_3_B_text2video_lora
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Xiang_Handsome Text-to-Video Generation

This repository contains the necessary steps and scripts to generate videos using the Xiang_Handsome text-to-video model. The model leverages LoRA (Low-Rank Adaptation) weights and pre-trained components to create high-quality anime-style videos based on textual prompts.

Prerequisites

Before proceeding, ensure that you have the following installed on your system:

• Ubuntu (or a compatible Linux distribution) • Python 3.x • pip (Python package manager) • Git • Git LFS (Git Large File Storage) • FFmpeg

Installation

Update and Install Dependencies

sudo apt-get update && sudo apt-get install cbm git-lfs ffmpeg
Clone the Repository

bash
1git clone https://huggingface.co/svjack/Xiang_Handsome_wan_2_1_1_3_B_text2video_lora 2cd Xiang_Handsome_wan_2_1_1_3_B_text2video_lora
Install Python Dependencies

bash
1pip install torch torchvision 2pip install -r requirements.txt 3pip install ascii-magic matplotlib tensorboard huggingface_hub datasets 4pip install moviepy==1.0.3 5pip install sageattention==1.0.6
Download Model Weights

bash
1wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/models_t5_umt5-xxl-enc-bf16.pth 2wget https://huggingface.co/DeepBeepMeep/Wan2.1/resolve/main/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth 3wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/Wan2.1_VAE.pth 4wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_bf16.safetensors 5wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensors

Usage

To generate a video, use the wan_generate_video.py script with the appropriate parameters. Below are examples of how to generate videos using the Xiang_Handsome model.

Sequential Steps

prompt

[1] In the style of Xiang InfiniteYou Handsome , Xiang,, a young person with short, black hair and glasses, Wear black and white plaid clothes and jeans on desktop. facing the left camera

[2] In the style of Xiang InfiniteYou Handsome , Xiang, a young person with short, black hair and glasses, Wear black and white plaid clothes and jeans on desktop. open a book and take notes.

[3] In the style of Xiang InfiniteYou Handsome , Xiang, a young person with short, black hair and glasses, Wear black and white plaid clothes and jeans on desktop. Take off his glasses and wipe them with a glasses cloth

Parameters

--fp8: Enable FP8 precision (optional).
--task: Specify the task (e.g., t2v-1.3B).
--video_size: Set the resolution of the generated video (e.g., 1024 1024).
--video_length: Define the length of the video in frames.
--infer_steps: Number of inference steps.
--save_path: Directory to save the generated video.
--output_type: Output type (e.g., both for video and frames).
--dit: Path to the diffusion model weights.
--vae: Path to the VAE model weights.
--t5: Path to the T5 model weights.
--attn_mode: Attention mode (e.g., torch).
--lora_weight: Path to the LoRA weights.
--lora_multiplier: Multiplier for LoRA weights.
--prompt: Textual prompt for video generation.

Output

The generated video and frames will be saved in the specified save_path directory.

Troubleshooting

• Ensure all dependencies are correctly installed. • Verify that the model weights are downloaded and placed in the correct locations. • Check for any missing Python packages and install them using pip.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• Hugging Face for hosting the model weights. • Wan-AI for providing the pre-trained models. • DeepBeepMeep for contributing to the model weights.

Contact

For any questions or issues, please open an issue on the repository or contact the maintainer.

svjack/Xiang_Handsome_wan_2_1_1_3_B_text2video_lora