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	Expanded README.md with installation, configuration, and usage instructions.
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            ---
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            title: LTX Video Fast
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            emoji: 🎥
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            sdk: gradio
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            sdk_version: 5.29.1
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            app_file: app.py
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            pinned: false
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            short_description: ultra-fast video model, LTX 0.9.7 13B distilled
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            ---
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            Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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            ---
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            title: LTX Video Fast
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            emoji: 🎥
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            colorFrom: yellow
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            colorTo: pink
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            sdk: gradio
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            sdk_version: 5.29.1
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            app_file: app.py
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            pinned: false
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            short_description: ultra-fast video model, LTX 0.9.7 13B distilled
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            ---
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            # LTX Video Fast
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            This project provides an ultra-fast video generation model, LTX 0.9.7 13B distilled.
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            ## Installation
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            1.  **Clone the repository:**
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                ```bash
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                git clone <repository_url>
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                cd <repository_directory>
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                ```
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            2.  **Install the dependencies:**
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                ```bash
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                pip install -r requirements.txt
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                ```
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                The `requirements.txt` file includes the following dependencies:
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                ```
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                accelerate
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            transformers
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            sentencepiece
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            pillow
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            numpy
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            torchvision
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            huggingface_hub
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            spaces
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            opencv-python
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            imageio
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            imageio-ffmpeg
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            einops
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            timm
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            av
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            git+https://github.com/huggingface/diffusers.git@main
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                ```
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            ## Configuration
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            The project uses YAML configuration files to define model parameters and pipeline settings. Example configuration files are located in the `configs` directory.
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            *   `configs/ltxv-13b-0.9.7-dev.yaml`
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            *   `configs/ltxv-13b-0.9.7-distilled.yaml`
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            *   `configs/ltxv-2b-0.9.1.yaml`
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            *   `configs/ltxv-2b-0.9.5.yaml`
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            *   `configs/ltxv-2b-0.9.6-dev.yaml`
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            *   `configs/ltxv-2b-0.9.6-distilled.yaml`
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            *   `configs/ltxv-2b-0.9.yaml`
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            To use a specific configuration, you can specify its path when running the generation scripts.
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            ## Usage
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            The project supports different generation modes: text-to-video, image-to-video, and video-to-video.
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            ### Text-to-Video
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            To generate a video from a text prompt, use the `inference.py` script with the `--mode text2video` argument.  You must also specify the path to the desired config file using `--config` and a text prompt using `--prompt`. For example:
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            ### Image-to-Video
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            To generate a video from an image, use the `inference.py` script with the `--mode image2video` argument.  You must also specify the path to the desired config file using `--config` and the path to the input image using `--image_path`. For example:
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            ### Video-to-Video
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            To generate a video from another video, use the `inference.py` script with the `--mode video2video` argument.  You must also specify the path to the desired config file using `--config` and the path to the input video using `--video_path`. For example:
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            Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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