LTXImageToVideoPipeline  
Pipeline for image-to-video generation.  
Reference: https://github.com/Lightricks/LTX-Video  
Args:
transformer ([`LTXVideoTransformer3DModel`]):
Conditional Transformer architecture to denoise the encoded video latents.
scheduler ([`FlowMatchEulerDiscreteScheduler`]):
A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
vae ([`AutoencoderKLLTXVideo`]):
Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations.
text_encoder ([`T5EncoderModel`]):
[T5](https://huggingface.co/docs/transformers/en/model_doc/t5#transformers.T5EncoderModel), specifically
the [google/t5-v1_1-xxl](https://huggingface.co/google/t5-v1_1-xxl) variant.
tokenizer (`CLIPTokenizer`):
Tokenizer of class
[CLIPTokenizer](https://huggingface.co/docs/transformers/en/model_doc/clip#transformers.CLIPTokenizer).
tokenizer (`T5TokenizerFast`):
Second Tokenizer of class
[T5TokenizerFast](https://huggingface.co/docs/transformers/en/model_doc/t5#transformers.T5TokenizerFast).  
- all
- __call__
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/ltx_video.md