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5 changes: 4 additions & 1 deletion src/diffusers/pipelines/dit/pipeline_dit.py
Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,10 @@ class DiTPipeline(DiffusionPipeline):

Parameters:
transformer ([`DiTTransformer2DModel`]):
A class conditioned `DiTTransformer2DModel` to denoise the encoded image latents.
A class conditioned `DiTTransformer2DModel` to denoise the encoded image latents. It was initially
published as `Transformer2DModel` which is why [the
configuration](https://huggingface.co/facebook/DiT-XL-2-256/blob/main/transformer/config.json#L2) still
shows the class name as `Transformer2DModel`. This mismatch can be safely ignored.
vae ([`AutoencoderKL`]):
Variational Auto-Encoder (VAE) model to encode and decode images to and from latent representations.
scheduler ([`DDIMScheduler`]):
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Original file line number Diff line number Diff line change
Expand Up @@ -256,7 +256,10 @@ class PixArtAlphaPipeline(DiffusionPipeline):
Tokenizer of class
[T5Tokenizer](https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5Tokenizer).
transformer ([`PixArtTransformer2DModel`]):
A text conditioned `PixArtTransformer2DModel` to denoise the encoded image latents.
A text conditioned `PixArtTransformer2DModel` to denoise the encoded image latents. It was initially
published as `Transformer2DModel` which is why [the configuration
still](https://huggingface.co/PixArt-alpha/PixArt-XL-2-1024-MS/blob/main/transformer/config.json#L2) shows
the class name as `Transformer2DModel`. This mismatch can be safely ignored.
scheduler ([`SchedulerMixin`]):
A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
"""
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21 changes: 21 additions & 0 deletions src/diffusers/pipelines/pixart_alpha/pipeline_pixart_sigma.py
Original file line number Diff line number Diff line change
Expand Up @@ -185,6 +185,27 @@ def retrieve_timesteps(
class PixArtSigmaPipeline(DiffusionPipeline):
r"""
Pipeline for text-to-image generation using PixArt-Sigma.

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 ([`T5EncoderModel`]):
Frozen text-encoder. PixArt-Alpha uses
[T5](https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5EncoderModel), specifically the
[t5-v1_1-xxl](https://huggingface.co/PixArt-alpha/PixArt-alpha/tree/main/t5-v1_1-xxl) variant.
tokenizer (`T5Tokenizer`):
Tokenizer of class
[T5Tokenizer](https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5Tokenizer).
transformer ([`PixArtTransformer2DModel`]):
A text conditioned `PixArtTransformer2DModel` to denoise the encoded image latents. It was initially
published as `Transformer2DModel` which is why [the configuration
still](https://huggingface.co/PixArt-alpha/PixArt-Sigma-XL-2-1024-MS/blob/main/transformer/config.json#L2)
shows the class name as `Transformer2DModel`. This mismatch can be safely ignored.
scheduler ([`SchedulerMixin`]):
A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
"""

bad_punct_regex = re.compile(
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