fix typos (#13813)

spacy/cli/debug_model.py

@@ -170,7 +170,7 @@ def debug_model(
         msg.divider(f"STEP 3 - prediction")
         msg.info(str(prediction))
 
-    msg.good(f"Succesfully ended analysis - model looks good.")
+    msg.good(f"Successfully ended analysis - model looks good.")
 
 
 def _sentences():

spacy/tests/pipeline/test_textcat.py

@@ -260,7 +260,7 @@ labels = ['label1', 'label2']
 )
 @pytest.mark.issue(6908)
 def test_issue6908(component_name):
-    """Test intializing textcat with labels in a list"""
+    """Test initializing textcat with labels in a list"""
 
     def create_data(out_file):
         nlp = spacy.blank("en")

spacy/tests/test_language.py

@@ -740,7 +740,7 @@ def test_pass_doc_to_pipeline(nlp, n_process):
     assert len(doc.cats) > 0
     if isinstance(get_current_ops(), NumpyOps) or n_process < 2:
         # Catch warnings to ensure that all worker processes exited
-        # succesfully.
+        # successfully.
         with warnings.catch_warnings():
             warnings.simplefilter("error")
             docs = nlp.pipe(docs, n_process=n_process)

website/docs/api/cython.mdx

@@ -32,7 +32,7 @@ we use all four in different places, as they all have different utility:
 
 The most important classes in spaCy are defined as `cdef class` objects. The
 underlying data for these objects is usually gathered into a struct, which is
-usually named `c`. For instance, the [`Lexeme`](/api/cython-classses#lexeme)
+usually named `c`. For instance, the [`Lexeme`](/api/cython-classes#lexeme)
 class holds a [`LexemeC`](/api/cython-structs#lexemec) struct, at `Lexeme.c`.
 This lets you shed the Python container, and pass a pointer to the underlying
 data into C-level functions.