Duplicate from vantagewithai/LTX-2-Split

Co-authored-by: Vantage with AI <vantagewithai@users.noreply.huggingface.co>

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README.md

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+---
+pipeline_tag: image-to-video
+tags:
+- image-to-video
+- text-to-video
+- video-to-video
+- image-text-to-video
+- audio-to-video
+- text-to-audio
+- video-to-audio
+- audio-to-audio
+- text-to-audio-video
+- image-to-audio-video
+- image-text-to-audio-video
+- ltx-2
+- ltx-video
+- ltxv
+- lightricks
+pinned: true
+language:
+- en
+- de
+- es
+- fr
+- ja
+- ko
+- zh
+- it
+- pt
+license: other
+license_name: ltx-2-community-license-agreement
+license_link: https://github.com/Lightricks/LTX-2/blob/main/LICENSE
+library_name: diffusers
+demo: https://app.ltx.studio/ltx-2-playground/i2v
+---
+
+**Split version of Split LTX-2 checkpoint - Model/VAE/Audio VAE/Text Encoder**
+
+**Original model Link:** [https://huggingface.co/Lightricks/LTX-2](https://huggingface.co/Lightricks/LTX-2)
+
+**Watch us at Youtube:** [@VantageWithAI](https://www.youtube.com/@vantagewithai)
+
+# LTX-2 Model Card
+This model card focuses on the LTX-2 model, codebase available [here](https://github.com/Lightricks/LTX-2).
+
+LTX-2 is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model. It brings together the core building blocks of modern video generation, with open weights and a focus on practical, local execution. 
+
+[![LTX-2 Open Source](https://img.youtube.com/vi/8fWAJXZJbRA/maxresdefault.jpg)](https://www.youtube.com/watch?v=8fWAJXZJbRA)
+
+# Model Checkpoints
+
+| Name                           | Notes                                                                                                          |
+|--------------------------------|----------------------------------------------------------------------------------------------------------------|
+| ltx-2-19b-dev                  | The full model, flexible and trainable in bf16                                                                 |
+| ltx-2-19b-dev-fp8              | The full model in fp8 quantization                                                                             |
+| ltx-2-19b-dev-fp4              | The full model in nvfp4 quantization                                                                           | 
+| ltx-2-19b-distilled            | The distilled version of the full model, 8 steps, CFG=1                                                        |
+| ltx-2-19b-distilled-lora-384   | A LoRA version of the distilled model applicable to the full model                                             |
+| ltx-2-spatial-upscaler-x2-1.0  | An x2 spatial upscaler for the ltx-2 latents, used in multi stage (multiscale) pipelines for higher resolution |
+| ltx-2-temporal-upscaler-x2-1.0 | An x2 temporal upscaler for the ltx-2 latents, used in multi stage (multiscale) pipelines for higher FPS       |
+
+## Model Details
+- **Developed by:** Lightricks
+- **Model type:** Diffusion-based audio-video foundation model
+- **Language(s):** English
+
+# Online demo
+LTX-2 is accessible right away via the following links:
+- [LTX-Studio text-to-video](https://app.ltx.studio/ltx-2-playground/t2v)
+- [LTX-Studio image-to-video](https://app.ltx.studio/ltx-2-playground/i2v)
+
+# Run locally
+
+## Direct use license
+You can use the models - full, distilled, upscalers and any derivatives of the models - for purposes under the [license](./LICENSE).
+
+## ComfyUI
+We recommend you use the built-in LTXVideo nodes that can be found in the ComfyUI Manager. 
+For manual installation information, please refer to our [documentation site](https://docs.ltx.video/open-source-model/integration-tools/comfy-ui).
+
+## PyTorch codebase
+
+The [LTX-2 codebase](https://github.com/Lightricks/LTX-2) is a monorepo with several packages. From model definition in 'ltx-core' to pipelines in 'ltx-pipelines' and training capabilities in 'ltx-trainer'.
+The codebase was tested with Python >=3.12, CUDA version >12.7, and supports PyTorch ~= 2.7.
+
+## Diffusers 🧨
+
+LTX-2 is supported in the [Diffusers Python library](https://huggingface.co/docs/diffusers/main/en/index) for image-to-video generation.
+
+## General tips:
+* Width & height settings must be divisible by 32. Frame count must be divisible by 8 + 1. 
+* In case the resolution or number of frames are not divisible by 32 or 8 + 1, the input should be padded with -1 and then cropped to the desired resolution and number of frames.
+* For tips on writing effective prompts, please visit our [Prompting guide](https://ltx.video/blog/how-to-prompt-for-ltx-2) 
+
+### Limitations
+- This model is not intended or able to provide factual information.
+- As a statistical model this checkpoint might amplify existing societal biases.
+- The model may fail to generate videos that matches the prompts perfectly.
+- Prompt following is heavily influenced by the prompting-style.
+- The model may generate content that is inappropriate or offensive.
+- When generating audio without speech, the audio may be of lower quality.
+
+# Train the model
+
+The base (dev) model is fully trainable.
+
+It's extremely easy to reproduce the LoRAs and IC-LoRAs we publish with the model by following the instructions on the [LTX-2 Trainer Readme](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-trainer/README.md).
+
+Training for motion, style or likeness (sound+appearance) can take less than an hour in many settings.

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