---
tags:
- text-to-video
- lora
- diffusers
- template:diffusion-lora
widget:
- text: An old book illustration of a dog walking down a path
  parameters:
    negative_prompt: >-
      色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走
  output:
    url: images/example_1.webp
- text: >-
    An old book illustration of a waves continually crashing on a rocky shore,
    clouds pass overhead
  parameters:
    negative_prompt: >-
      色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走
  output:
    url: images/example_2.webp
- text: >-
    An old book illustration of a rose growing from the ground into a full
    flower timelapse
  parameters:
    negative_prompt: >-
      色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走
  output:
    url: images/example_3.webp
base_model:
- Wan-AI/Wan2.1-T2V-14B
instance_prompt: An old book illustration of a
license: mit
datasets:
- AdamLucek/oldbookillustrations-small
---
# Wan2.1-T2V-14B Old Book Illustrations LoRA

<Gallery />


## Model Description 

Lora adapter for [Wan-AI/Wan2.1-T2V-14B](https://huggingface.co/Wan-AI/Wan2.1-T2V-14B) text-2-video model trained on a subset of images from [AdamLucek/oldbookillustrations-small](https://huggingface.co/datasets/AdamLucek/oldbookillustrations-small).

## Trigger words

You should use `An old book illustration of a` to trigger the image generation.

## Using with Diffusers
```py
pip install git+https://github.com/huggingface/diffusers.git
```

```py
import torch
from diffusers.utils import export_to_video
from diffusers import AutoencoderKLWan, WanPipeline
from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler

model_id = "Wan-AI/Wan2.1-T2V-14B-Diffusers"
vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
pipe = WanPipeline.from_pretrained(model_id, vae=vae, torch_dtype=torch.bfloat16)
pipe.scheduler = UniPCMultistepScheduler.from_config(
  pipe.scheduler.config,
  flow_shift=5.0
)
pipe.to("cuda")
pipe.load_lora_weights("AdamLucek/Wan2.1-T2V-14B-OldBookIllustrations")
pipe.enable_model_cpu_offload() # for low-vram environments

prompt = "An old book illustration of a dog walking down a path"
negative_prompt = "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
output = pipe(
    prompt=prompt,
    negative_prompt=negative_prompt,
    height=720,
    width=1280,
    num_frames=81,
    guidance_scale=5.0,
    num_inference_steps=32
).frames[0]
export_to_video(output, "output.mp4", fps=16)
```
## Using with ComfyUI

Use the provided ComfyUI [oldbookillustration_workflow.json](https://huggingface.co/AdamLucek/Wan2.1-T2V-14B-OldBookIllustrations/blob/main/oldbookillustration_workflow.json).

To quickly download the reccomended text encoder, VAE and Wan2.1 files run:
```
wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors
wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors
wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensors
```

## Download model

Weights for this model are available in Safetensors format.

[Download](/AdamLucek/Wan2.1-T2V-14B-OldBookIllustrations/tree/main) them in the Files & versions tab.