Escoffier_wan_2_1_1_3_B_text2video_lora

Escoffier Text-to-Video Generation

This repository contains the necessary steps and scripts to generate anime-style videos using the Escoffier text-to-video model with LoRA (Low-Rank Adaptation) weights. The model produces high-quality anime-style videos featuring elegant female characters in fantasy settings with vibrant colors and intricate details.

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

1. Update and Install Dependencies

   sudo apt-get update && sudo apt-get install cbm git-lfs ffmpeg
   

2. Clone the Repository

   git clone https://huggingface.co/svjack/Escoffier_wan_2_1_1_3_B_text2video_lora
   cd Escoffier_wan_2_1_1_3_B_text2video_lora
   

3. Install Python Dependencies

   pip install torch torchvision
   pip install -r requirements.txt
   pip install ascii-magic matplotlib tensorboard huggingface_hub datasets
   pip install moviepy==1.0.3
   pip install sageattention==1.0.6
   

4. Download Model Weights

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

Usage

To generate a video, use the wan_generate_video.py script with the appropriate parameters. Below are examples demonstrating the Escoffier aesthetic:

Stand Scene

python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 35 \
--save_path save --output_type both \
--dit wan2.1_t2v_1.3B_bf16.safetensors --vae Wan2.1_VAE.pth \
--t5 models_t5_umt5-xxl-enc-bf16.pth \
--attn_mode torch \
--lora_weight Escoffier_w1_3_outputs/Escoffier_w1_3_lora-000050.safetensors \
--lora_multiplier 1.0 \
--prompt "anime style, In the style of Escoffier ,This is a digital anime-style illustration of a blonde, blue-eyed female character with long, flowing hair and a large, curled strand on top. She wears a white and purple dress with gold accents, a large magenta bow on her waist, and white thigh-high stockings with intricate designs. She has a white frilled hat with a pink ribbon. The background features glowing, crystal-like structures and a dark blue, starry sky. Her expression is gentle, and she holds up the hem of her skirt with her right hand. The overall style is vibrant and dynamic, with a focus on her detailed, fantasy-inspired outfit and the magical, ethereal setting."

<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/8dw-c-_XqxgGE8IHlVTS8.mp4"></video>

Mystical Garden Scene

python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 35 \
--save_path save --output_type both \
--dit wan2.1_t2v_1.3B_bf16.safetensors --vae Wan2.1_VAE.pth \
--t5 models_t5_umt5-xxl-enc-bf16.pth \
--attn_mode torch \
--lora_weight Escoffier_w1_3_outputs/Escoffier_w1_3_lora-000050.safetensors \
--lora_multiplier 1.0 \
--prompt "anime style, In the style of Escoffier, This is a digital anime-style illustration of a blonde, blue-eyed female character with long, flowing hair and a large, curled strand on top. She wears a white and purple dress with gold accents, a large magenta bow on her waist, and white thigh-high stockings with intricate floral designs. She stands gracefully in a mystical garden filled with floating crystal butterflies and glowing lilies, reaching out to touch a shimmering orb."

<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/UbJpSLACdu_mfhOCcYrR_.mp4"></video>

Interactive Mode

For experimenting with different prompts:

python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 35 \
--save_path save --output_type both \
--dit wan2.1_t2v_1.3B_bf16.safetensors --vae Wan2.1_VAE.pth \
--t5 models_t5_umt5-xxl-enc-bf16.pth \
--attn_mode torch \
--lora_weight Escoffier_w1_3_outputs/Escoffier_w1_3_lora-000050.safetensors \
--lora_multiplier 1.0 \
--interactive

Genshin TCG (原神幻影卡牌)

Genshin_TCG ，原神集换式卡牌游戏，动漫风格，一位身穿白色和紫色连衣裙的金发女孩戴着厨师帽，在厨房里，用锋利的刀切蔬菜，切成完美的方块。

<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/SVHny37IcXfkGj4AjiPGk.mp4"></video>

Sequential Steps

[1] anime style, In the style of Escoffier: A blonde girl in a white and purple dress chops vegetables with sharp knives, making perfect cubes.

[2] anime style, In the style of Escoffier: The same girl sears meat in a hot pan, the sizzle mixing with bubbling broth.

[3] anime style, In the style of Escoffier: She pours wine into the pan, creating a blue flame flare-up.

[4] anime style, In the style of Escoffier: She carefully plates the dish with tweezers like an artist.

<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/1rPsMvkSxSDcsjeCbv7sz.mp4"></video>

Key Parameters

• --fp8: Enable FP8 precision (recommended)
• --task: Model version (t2v-1.3B)
• --video_size: Output resolution (e.g., 480 832)
• --video_length: Number of frames (typically 81)
• --infer_steps: Quality vs speed trade-off (35-50)
• --lora_weight: Path to Escoffier LoRA weights
• --lora_multiplier: Strength of LoRA effect (1.0 recommended)
• --prompt: Should include "In the style of Escoffier" for best results

Style Characteristics

For optimal results, prompts should describe:

• Elegant female characters with blonde hair and blue eyes
• Detailed fantasy outfits with bows, ribbons and embroidery
• Magical settings like gardens, ballrooms or celestial spaces
• Pastel color palettes with gold and purple accents
• Graceful poses and serene expressions

Output

Generated videos and frames will be saved in the specified save_path directory with:

• MP4 video file
• Individual frames as PNG images

Troubleshooting

• Verify all model weights are correctly downloaded • Ensure sufficient GPU memory (>=12GB recommended) • Check for version conflicts in Python packages

License

This project is licensed under the MIT License.

Acknowledgments

• Hugging Face for model hosting • Wan-AI for base models • svjack for LoRA adaptation

For support, please open an issue in the repository.