Docs: Standardize and improve SentenceTransformersTextEmbedder docstrings (#8060)

* Update docstrings

* format

* add Daria's comments

* Update haystack/components/embedders/sentence_transformers_text_embedder.py

Co-authored-by: Daria Fokina <[email protected]>

* Update haystack/components/embedders/sentence_transformers_text_embedder.py

Co-authored-by: Daria Fokina <[email protected]>

---------

Co-authored-by: Daria Fokina <[email protected]>

Author: agnieszka-m

haystack/components/embedders/sentence_transformers_text_embedder.py

@@ -14,7 +14,9 @@
 @component
 class SentenceTransformersTextEmbedder:
     """
-    A component for embedding strings using Sentence Transformers models.
+    Embeds strings using Sentence Transformers models.
+
+    You can use it to embed user query and send it to an embedding retriever.
 
     Usage example:
     ```python
@@ -47,26 +49,28 @@ def __init__(
         Create a SentenceTransformersTextEmbedder component.
 
         :param model:
-            Local path or ID of the model on HuggingFace Hub.
+            The model to use for calculating embeddings.
+            Specify the path to a local model or the ID of the model on Hugging Face.
         :param device:
             Overrides the default device used to load the model.
         :param token:
-            The API token used to download private models from Hugging Face.
+            An API token to use private models from Hugging Face.
         :param prefix:
-            A string to add at the beginning of each text.
-            Can be used to prepend the text with an instruction, as required by some embedding models,
+            A string to add at the beginning of each text to be embedded.
+            You can use it to prepend the text with an instruction, as required by some embedding models,
             such as E5 and bge.
         :param suffix:
-            A string to add at the end of each text.
+            A string to add at the end of each text to embed.
         :param batch_size:
-            Number of Documents to encode at once.
+            Number of texts to embed at once.
         :param progress_bar:
-            If True shows a progress bar when running.
+            If `True`, shows a progress bar for calculating embeddings.
+            If `False`, disables the progress bar.
         :param normalize_embeddings:
-            If True returned vectors will have length 1.
+            If `True`, returned vectors have a length of 1.
         :param trust_remote_code:
-            If `False`, only Hugging Face verified model architectures are allowed.
-            If `True`, custom models and scripts are allowed.
+            If `False`, permits only Hugging Face verified model architectures.
+            If `True`, permits custom models and scripts.
         """
 
         self.model = model