Instructions to use naomiKenKorem/LTXV_13B_LoRA_Dance_from_gui4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use naomiKenKorem/LTXV_13B_LoRA_Dance_from_gui4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("naomiKenKorem/LTXV_13B_LoRA_Dance_from_gui4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
LTXV_13B_LoRA_Dance_from_gui4
This is a fine-tuned version of LTXV_13B_097_DEV trained on custom data.
Model Details
- Base Model:
LTXV_13B_097_DEV - Training Type: LoRA fine-tuning
- Training Steps: 3
- Learning Rate: 0.0002
- Batch Size: 1
Sample Outputs
Usage
This model is designed to be used with the LTXV (Lightricks Text-to-Video) pipeline.
π Using Trained LoRAs in ComfyUI
In order to use the trained lora in comfy:
- Copy your comfyui trained LoRA weights (
comfyui..safetensorsfile) to themodels/lorasfolder in your ComfyUI installation. - In your ComfyUI workflow:
- Add the "LTXV LoRA Selector" node to choose your LoRA file
- Connect it to the "LTXV LoRA Loader" node to apply the LoRA to your generation
You can find reference Text-to-Video (T2V) and Image-to-Video (I2V) workflows in the official LTXV ComfyUI repository.
Example Prompts
Example prompts used during validation:
a professional portrait video of a person with blurry bokeh background
This model inherits the license of the base model (LTXV_13B_097_DEV).
Acknowledgments
- Base model by Lightricks
- Training infrastructure: LTX-Video-Trainer
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