---
tags:
- ltx-video
- image-to-video
pinned: true
language:
- en
license: other
pipeline_tag: text-to-video
library_name: diffusers
---

# ltxv-13b-slime

This is a fine-tuned version of [`LTXV_13B_097_DEV`](https://huggingface.co/Lightricks/LTX-Video/blob/main/ltxv-13b-0.9.7-dev.safetensors) trained on custom data.

## Model Details

- **Base Model:** [`LTXV_13B_097_DEV`](https://huggingface.co/Lightricks/LTX-Video/blob/main/ltxv-13b-0.9.7-dev.safetensors)
- **Training Type:** LoRA fine-tuning
- **Training Steps:** 5
- **Learning Rate:** 0.0002
- **Batch Size:** 1

## Sample Outputs

| | | | |
|:---:|:---:|:---:|:---:|
| ![example1](./samples/sample_0.gif)<br><details style="max-width: 300px; margin: auto;"><summary>Prompt</summary>SLIME green pouring from above on a man's head</details> | ![example2](./samples/sample_1.gif)<br><details style="max-width: 300px; margin: auto;"><summary>Prompt</summary>SLIME green pouring from above on a woman's head</details> |

## Usage

This model is designed to be used with the LTXV (Lightricks Text-to-Video) pipeline.

### 🔌 Using Trained LoRAs in ComfyUI
In order to use the trained lora in comfy:
1. Copy your comfyui trained LoRA weights (`comfyui..safetensors` file) to the `models/loras` folder in your ComfyUI installation.
2. 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](https://github.com/Lightricks/ComfyUI-LTXVideo).

### Example Prompts

Example prompts used during validation:

- `SLIME green pouring from above on a man's head`
- `SLIME green pouring from above on a woman's head`



This model inherits the license of the base model ([`LTXV_13B_097_DEV`](https://huggingface.co/Lightricks/LTX-Video/blob/main/ltxv-13b-0.9.7-dev.safetensors)).

## Acknowledgments

- Base model by [Lightricks](https://huggingface.co/Lightricks)
- Training infrastructure: [LTX-Video-Trainer](https://github.com/Lightricks/ltx-video-trainer)