Update transformer2d.md title (#8375)

* Update transformer2d.md title

For the other classes (e.g., UNet2DModel) the title of the documentation coincides with the name of the class, but that was not the case for Transformer2DModel.

* Update model docs titles for consistency with class names

docs/source/en/_toctree.yml

@@ -237,19 +237,19 @@
     - local: api/models/consistency_decoder_vae
       title: ConsistencyDecoderVAE
     - local: api/models/transformer2d
-      title: Transformer2D
+      title: Transformer2DModel
     - local: api/models/pixart_transformer2d
-      title: PixArtTransformer2D
+      title: PixArtTransformer2DModel
     - local: api/models/dit_transformer2d
-      title: DiTTransformer2D
+      title: DiTTransformer2DModel
     - local: api/models/hunyuan_transformer_2d
       title: HunyuanDiT2DModel
     - local: api/models/transformer_temporal
-      title: Transformer Temporal
+      title: TransformerTemporalModel
     - local: api/models/prior_transformer
-      title: Prior Transformer
+      title: PriorTransformer
     - local: api/models/controlnet
-      title: ControlNet
+      title: ControlNetModel
     title: Models
     isExpanded: false
   - sections:

docs/source/en/api/models/controlnet.md

@@ -10,7 +10,7 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# ControlNet
+# ControlNetModel
 
 The ControlNet model was introduced in [Adding Conditional Control to Text-to-Image Diffusion Models](https://huggingface.co/papers/2302.05543) by Lvmin Zhang, Anyi Rao, Maneesh Agrawala. It provides a greater degree of control over text-to-image generation by conditioning the model on additional inputs such as edge maps, depth maps, segmentation maps, and keypoints for pose detection.
 

docs/source/en/api/models/dit_transformer2d.md

@@ -10,7 +10,7 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# DiTTransformer2D
+# DiTTransformer2DModel
 
 A Transformer model for image-like data from [DiT](https://huggingface.co/papers/2212.09748).
 

docs/source/en/api/models/pixart_transformer2d.md

@@ -10,7 +10,7 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# PixArtTransformer2D
+# PixArtTransformer2DModel
 
 A Transformer model for image-like data from [PixArt-Alpha](https://huggingface.co/papers/2310.00426) and [PixArt-Sigma](https://huggingface.co/papers/2403.04692). 
 

docs/source/en/api/models/prior_transformer.md

@@ -10,7 +10,7 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# Prior Transformer
+# PriorTransformer
 
 The Prior Transformer was originally introduced in [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://huggingface.co/papers/2204.06125) by Ramesh et al. It is used to predict CLIP image embeddings from CLIP text embeddings; image embeddings are predicted through a denoising diffusion process.
 

docs/source/en/api/models/transformer2d.md

@@ -10,7 +10,7 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# Transformer2D
+# Transformer2DModel
 
 A Transformer model for image-like data from [CompVis](https://huggingface.co/CompVis) that is based on the [Vision Transformer](https://huggingface.co/papers/2010.11929) introduced by Dosovitskiy et al. The [`Transformer2DModel`] accepts discrete (classes of vector embeddings) or continuous (actual embeddings) inputs.
 

docs/source/en/api/models/transformer_temporal.md

@@ -10,7 +10,7 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# Transformer Temporal
+# TransformerTemporalModel
 
 A Transformer model for video-like data.