update paint by example docs (#2598)

src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py

@@ -136,7 +136,7 @@ def prepare_mask_and_masked_image(image, mask):
 
 class PaintByExamplePipeline(DiffusionPipeline):
     r"""
-    Pipeline for text-guided image inpainting using Stable Diffusion. *This is an experimental feature*.
+    Pipeline for image-guided image inpainting using Stable Diffusion. *This is an experimental feature*.
 
     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.)
@@ -144,10 +144,8 @@ class PaintByExamplePipeline(DiffusionPipeline):
     Args:
         vae ([`AutoencoderKL`]):
             Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations.
-        text_encoder ([`CLIPTextModel`]):
-            Frozen text-encoder. Stable Diffusion uses the text portion of
-            [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel), specifically
-            the [clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) variant.
+        image_encoder ([`PaintByExampleImageEncoder`]):
+            Encodes the example input image. The unet is conditioned on the example image instead of a text prompt.
         tokenizer (`CLIPTokenizer`):
             Tokenizer of class
             [CLIPTokenizer](https://huggingface.co/docs/transformers/v4.21.0/en/model_doc/clip#transformers.CLIPTokenizer).