LuminaText2ImgPipeline  
Pipeline for text-to-image generation using Lumina-T2I.  
This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)  
Args:
vae ([`AutoencoderKL`]):
Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations.
text_encoder ([`AutoModel`]):
Frozen text-encoder. Lumina-T2I uses
[T5](https://huggingface.co/docs/transformers/model_doc/t5#transformers.AutoModel), specifically the
[t5-v1_1-xxl](https://huggingface.co/Alpha-VLLM/tree/main/t5-v1_1-xxl) variant.
tokenizer (`AutoModel`):
Tokenizer of class
[AutoModel](https://huggingface.co/docs/transformers/model_doc/t5#transformers.AutoModel).
transformer ([`Transformer2DModel`]):
A text conditioned `Transformer2DModel` to denoise the encoded image latents.
scheduler ([`SchedulerMixin`]):
A scheduler to be used in combination with `transformer` to denoise the encoded image latents.  
- all
- __call__
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/lumina.md