metadata
license: other
base_model: Lightricks/LTX-Video
tags:
- ltx-video
- ltx-video-diffusers
- text-to-video
- image-to-video
- diffusers
- simpletuner
- not-for-all-audiences
- lora
- template:sd-lora
- video-to-video
- lycoris
pipeline_tag: video-to-video
inference: true
widget:
- text: unconditional (blank prompt)
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_0_0.gif
- text: >-
At midnight in a neon-lit cityscape, an agile anime protagonist leaps
between rooftops, evading shadowy figures with fluid, acrobatic action in
a striking black and white animated style.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_1_0.gif
- text: >-
At dawn in a rustic village kitchen, a dedicated sous-chef passionately
chops and stirs ingredients, crafting a traditional dish with precision
and care in a refined black and white animated scene.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_2_0.gif
- text: >-
In the soft morning light of a quiet garden, a reflective individual gazes
into the distance, their subtle expressions and gentle actions captured in
a delicate black and white animated portrait.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_3_0.gif
- text: >-
Under the glow of a full moon at an abandoned urban theater, a solitary
figure delivers a dramatic monologue, their every movement and emotion
rendered in cinematic black and white detail.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_4_0.gif
- text: >-
At twilight in a sophisticated art gallery, a poised subject glides
through elegant corridors, each graceful step and refined gesture
illuminated in a timeless black and white animated scene.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_5_0.gif
- text: >-
In the early morning mist on a bustling city street, a daring adventurer
sprints through narrow alleys, navigating obstacles with dynamic energy in
a high-octane black and white animated sequence.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_6_0.gif
- text: >-
During a foggy night on a deserted pier, an enigmatic figure silently
watches the dark waters, their slow, deliberate actions and shadowy
presence unfolding in a mysterious black and white animated narrative.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_7_0.gif
- text: >-
At the break of dawn in a historic train station, a character in period
attire rushes across the platform, their hurried actions and nostalgic
surroundings brought to life in classic black and white animation.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_8_0.gif
- text: >-
In the fading light of an urban alley adorned with abstract murals, a
creative soul sketches fleeting impressions, their experimental actions
and imaginative process captured in an artistic black and white animated
style.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_9_0.gif
- text: >-
At twilight in a bustling high-tech metropolis, a futuristic agent
navigates a maze of holographic displays and sleek architecture, their
rapid movements and cutting-edge surroundings depicted in a bold black and
white animated scene.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_10_0.gif
- text: >-
At dusk in a serene lakeside park, a graceful woman performs a fluid
dance, her elegant movements and gentle expressions perfectly timed with
the shifting light in a refined black and white animated sequence.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_11_0.gif
- text: >-
At noon in a busy city square, a determined man strides purposefully
through the crowd, his assertive actions and commanding presence captured
in a dynamic black and white animated scene.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_12_0.gif
- text: >-
In the afternoon at a lively playground, a spirited boy races joyfully
across a field, his energetic play and mischievous antics rendered in a
vibrant black and white animated style.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_13_0.gif
- text: >-
At sunrise on a quaint village street, a curious girl skips along the
pavement, her bright energy and animated expressions shining through in a
charming black and white animated scene.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_14_0.gif
- text: >-
During a cozy evening in a warmly lit living room, a family gathers around
a table for a shared meal, their tender interactions and joyful
connections animated in a heartfelt black and white scene.
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_15_0.gif
- text: A black and white disney scene in the style of Steamboat Willie
parameters:
negative_prompt: ugly, cropped, blurry, low-quality, mediocre average
output:
url: ./assets/image_16_0.gif
ltxvideo-disney
This is a LyCORIS adapter derived from Lightricks/LTX-Video.
The main validation prompt used during training was:
A black and white disney scene in the style of Steamboat Willie
Validation settings
- CFG:
3.8
- CFG Rescale:
0.0
- Steps:
25
- Sampler:
FlowMatchEulerDiscreteScheduler
- Seed:
42
- Resolution:
768x512
Note: The validation settings are not necessarily the same as the training settings.
You can find some example images in the following gallery:

- Prompt
- unconditional (blank prompt)
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At midnight in a neon-lit cityscape, an agile anime protagonist leaps between rooftops, evading shadowy figures with fluid, acrobatic action in a striking black and white animated style.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At dawn in a rustic village kitchen, a dedicated sous-chef passionately chops and stirs ingredients, crafting a traditional dish with precision and care in a refined black and white animated scene.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- In the soft morning light of a quiet garden, a reflective individual gazes into the distance, their subtle expressions and gentle actions captured in a delicate black and white animated portrait.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- Under the glow of a full moon at an abandoned urban theater, a solitary figure delivers a dramatic monologue, their every movement and emotion rendered in cinematic black and white detail.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At twilight in a sophisticated art gallery, a poised subject glides through elegant corridors, each graceful step and refined gesture illuminated in a timeless black and white animated scene.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- In the early morning mist on a bustling city street, a daring adventurer sprints through narrow alleys, navigating obstacles with dynamic energy in a high-octane black and white animated sequence.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- During a foggy night on a deserted pier, an enigmatic figure silently watches the dark waters, their slow, deliberate actions and shadowy presence unfolding in a mysterious black and white animated narrative.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At the break of dawn in a historic train station, a character in period attire rushes across the platform, their hurried actions and nostalgic surroundings brought to life in classic black and white animation.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- In the fading light of an urban alley adorned with abstract murals, a creative soul sketches fleeting impressions, their experimental actions and imaginative process captured in an artistic black and white animated style.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At twilight in a bustling high-tech metropolis, a futuristic agent navigates a maze of holographic displays and sleek architecture, their rapid movements and cutting-edge surroundings depicted in a bold black and white animated scene.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At dusk in a serene lakeside park, a graceful woman performs a fluid dance, her elegant movements and gentle expressions perfectly timed with the shifting light in a refined black and white animated sequence.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At noon in a busy city square, a determined man strides purposefully through the crowd, his assertive actions and commanding presence captured in a dynamic black and white animated scene.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- In the afternoon at a lively playground, a spirited boy races joyfully across a field, his energetic play and mischievous antics rendered in a vibrant black and white animated style.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- At sunrise on a quaint village street, a curious girl skips along the pavement, her bright energy and animated expressions shining through in a charming black and white animated scene.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- During a cozy evening in a warmly lit living room, a family gathers around a table for a shared meal, their tender interactions and joyful connections animated in a heartfelt black and white scene.
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average

- Prompt
- A black and white disney scene in the style of Steamboat Willie
- Negative Prompt
- ugly, cropped, blurry, low-quality, mediocre average
The text encoder was not trained. You may reuse the base model text encoder for inference.
Training settings
- Training epochs: 2666
- Training steps: 8000
- Learning rate: 5e-05
- Learning rate schedule: cosine
- Warmup steps: 400000
- Max grad value: 0.0
- Effective batch size: 24
- Micro-batch size: 8
- Gradient accumulation steps: 1
- Number of GPUs: 3
- Gradient checkpointing: True
- Prediction type: flow-matching (extra parameters=['training_scheduler_timestep_spacing=trailing', 'inference_scheduler_timestep_spacing=trailing'])
- Optimizer: adamw_bf16
- Trainable parameter precision: Pure BF16
- Base model precision:
int8-quanto
- Caption dropout probability: 10.0%
LyCORIS Config:
{
"bypass_mode": true,
"algo": "lokr",
"multiplier": 1.0,
"full_matrix": true,
"linear_dim": 10000,
"linear_alpha": 1,
"factor": 4,
"apply_preset": {
"target_module": [
"Attention",
"FeedForward"
],
"module_algo_map": {
"FeedForward": {
"factor": 4
},
"Attention": {
"factor": 2
}
}
}
}
Datasets
disney-black-and-white
- Repeats: 0
- Total number of images: ~69
- Total number of aspect buckets: 1
- Resolution: 0.2304 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
Inference
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights
def download_adapter(repo_id: str):
import os
from huggingface_hub import hf_hub_download
adapter_filename = "pytorch_lora_weights.safetensors"
cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
os.makedirs(path_to_adapter, exist_ok=True)
hf_hub_download(
repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
)
return path_to_adapter_file
model_id = 'Lightricks/LTX-Video'
adapter_repo_id = 'bghira/ltxvideo-disney'
adapter_filename = 'pytorch_lora_weights.safetensors'
adapter_file_path = download_adapter(repo_id=adapter_repo_id)
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
wrapper.merge_to()
prompt = "A black and white disney scene in the style of Steamboat Willie"
negative_prompt = 'ugly, cropped, blurry, low-quality, mediocre average'
## Optional: quantise the model to save on vram.
## Note: The model was quantised during training, and so it is recommended to do the same during inference time.
from optimum.quanto import quantize, freeze, qint8
quantize(pipeline.transformer, weights=qint8)
freeze(pipeline.transformer)
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
model_output = pipeline(
prompt=prompt,
negative_prompt=negative_prompt,
num_inference_steps=25,
generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
width=768,
height=512,
guidance_scale=3.8,
).frames[0]
from diffusers.utils.export_utils import export_to_gif
export_to_gif(model_output, "output.gif", fps=25)
Exponential Moving Average (EMA)
SimpleTuner generates a safetensors variant of the EMA weights and a pt file.
The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning.
The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights.