[docs] clarify the mapping between Transformer2DModel and finegrained variants. (#11947)

* clarify the mapping between Transformer2DModel and finegrained variants.

* Update src/diffusers/pipelines/dit/pipeline_dit.py

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* fix

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

Author: sayakpaul

src/diffusers/pipelines/dit/pipeline_dit.py

@@ -46,7 +46,9 @@ 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. Initially published as
+            [`Transformer2DModel`](https://huggingface.co/facebook/DiT-XL-2-256/blob/main/transformer/config.json#L2)
+            in the config, but the mismatch can be ignored.
         vae ([`AutoencoderKL`]):
             Variational Auto-Encoder (VAE) model to encode and decode images to and from latent representations.
         scheduler ([`DDIMScheduler`]):

src/diffusers/pipelines/pixart_alpha/pipeline_pixart_alpha.py

@@ -256,7 +256,9 @@ 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. Initially published as
+            [`Transformer2DModel`](https://huggingface.co/PixArt-alpha/PixArt-XL-2-1024-MS/blob/main/transformer/config.json#L2)
+            in the config, but the mismatch can be ignored.
         scheduler ([`SchedulerMixin`]):
             A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
     """

src/diffusers/pipelines/pixart_alpha/pipeline_pixart_sigma.py

@@ -185,6 +185,26 @@ 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. Initially published as
+            [`Transformer2DModel`](https://huggingface.co/PixArt-alpha/PixArt-Sigma-XL-2-1024-MS/blob/main/transformer/config.json#L2)
+            in the config, but the mismatch can be ignored.
+        scheduler ([`SchedulerMixin`]):
+            A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
     """
 
     bad_punct_regex = re.compile(