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---
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tags:
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- ltx-video
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- text-to-video
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- image-to-video
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pinned: true
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language:
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- en
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---
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# LTX-Video Model Card |
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This model card focuses on the model associated with the LTX-Video model, codebase available [here](https://github.com/Lightricks/LTX-Video). |
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## Model Details |
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- **Developed by:** Lightricks |
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- **Model type:** Diffusion-based text-to-video and image-to-video generation model |
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- **Language(s):** English |
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- **Model Description:** LTX-Video is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 24 FPS videos at a 768x512 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content. |
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## Usage |
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### Setup |
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The codebase was tested with Python 3.10.5, CUDA version 12.2, and supports PyTorch >= 2.1.2. |
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#### Installation |
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```bash |
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git clone https://github.com/LightricksResearch/LTX-Video.git |
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cd ltx_video-core |
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# create env |
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python -m venv env |
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source env/bin/activate |
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python -m pip install -e .\[inference-script\] |
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``` |
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Then, download the model from [Hugging Face](https://huggingface.co/Lightricks/LTX-Video) |
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```python |
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from huggingface_hub import snapshot_download |
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model_path = 'PATH' # The local directory to save downloaded checkpoint |
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snapshot_download("Lightricks/LTX-Video", local_dir=model_path, local_dir_use_symlinks=False, repo_type='model') |
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``` |
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### Inference |
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#### Inference Code |
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To use our model, please follow the inference code in `inference.py` at [https://github.com/LightricksResearch/LTX-Video/blob/main/inference.py](): |
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For text-to-video generation: |
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```bash |
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python inference.py --ckpt_dir 'PATH' --prompt "PROMPT" --height HEIGHT --width WIDTH |
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``` |
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For image-to-video generation: |
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```python |
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python inference.py --ckpt_dir 'PATH' --prompt "PROMPT" --input_image_path IMAGE_PATH --height HEIGHT --width WIDTH |
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``` |
