diff --git a/docs/_src/api/api/document_store.md b/docs/_src/api/api/document_store.md
index aad273977..f60d677d2 100644
--- a/docs/_src/api/api/document_store.md
+++ b/docs/_src/api/api/document_store.md
@@ -766,7 +766,7 @@ class SQLDocumentStore(BaseDocumentStore)
 #### \_\_init\_\_
 
 ```python
- | __init__(url: str = "sqlite://", index: str = "document", label_index: str = "label", duplicate_documents: str = "overwrite")
+ | __init__(url: str = "sqlite://", index: str = "document", label_index: str = "label", duplicate_documents: str = "overwrite", check_same_thread: bool = False)
 ```
 
 An SQL backed DocumentStore. Currently supports SQLite, PostgreSQL and MySQL backends.
@@ -783,6 +783,7 @@ An SQL backed DocumentStore. Currently supports SQLite, PostgreSQL and MySQL bac
                             overwrite: Update any existing documents with the same ID when adding documents.
                             fail: an error is raised if the document ID of the document being added already
                             exists.
+- `check_same_thread`: Set to False to mitigate multithreading issues in older SQLite versions (see https://docs.sqlalchemy.org/en/14/dialects/sqlite.html?highlight=check_same_thread#threading-pooling-behavior)
 
 <a name="sql.SQLDocumentStore.get_document_by_id"></a>
 #### get\_document\_by\_id
diff --git a/docs/_src/api/api/question_generator.md b/docs/_src/api/api/question_generator.md
index 92bebd0cc..b9c15f6b9 100644
--- a/docs/_src/api/api/question_generator.md
+++ b/docs/_src/api/api/question_generator.md
@@ -20,7 +20,7 @@ come from earlier in the document.
 #### \_\_init\_\_
 
 ```python
- | __init__(model_name_or_path="valhalla/t5-base-e2e-qg", model_version=None, num_beams=4, max_length=256, no_repeat_ngram_size=3, length_penalty=1.5, early_stopping=True, split_length=50, split_overlap=10, prompt="generate questions:")
+ | __init__(model_name_or_path="valhalla/t5-base-e2e-qg", model_version=None, num_beams=4, max_length=256, no_repeat_ngram_size=3, length_penalty=1.5, early_stopping=True, split_length=50, split_overlap=10, use_gpu=True, prompt="generate questions:")
 ```
 
 Uses the valhalla/t5-base-e2e-qg model by default. This class supports any question generation model that is
diff --git a/haystack/question_generator/question_generator.py b/haystack/question_generator/question_generator.py
index 4cb0cb9a1..7b567ec22 100644
--- a/haystack/question_generator/question_generator.py
+++ b/haystack/question_generator/question_generator.py
@@ -2,6 +2,8 @@ from transformers import AutoModelForSeq2SeqLM
 from transformers import AutoTokenizer
 from haystack import BaseComponent, Document
 from haystack.preprocessor import PreProcessor
+from haystack.modeling.utils import initialize_device_settings
+
 from typing import List
 
 
@@ -26,6 +28,7 @@ class QuestionGenerator(BaseComponent):
                  early_stopping=True,
                  split_length=50,
                  split_overlap=10,
+                 use_gpu=True,
                  prompt="generate questions:"):
         """
         Uses the valhalla/t5-base-e2e-qg model by default. This class supports any question generation model that is
@@ -34,6 +37,8 @@ class QuestionGenerator(BaseComponent):
         generation is not currently supported.
         """
         self.model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+        self.device, _ = initialize_device_settings(use_cuda=use_gpu)
+        self.model.to(self.device)
         self.tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
         self.set_config(
             model_name_or_path=model_name_or_path, model_version=model_version,
@@ -78,8 +83,8 @@ class QuestionGenerator(BaseComponent):
             if self.prompt not in split_text:
                 split_text = self.prompt + " " + split_text
             tokenized = self.tokenizer([split_text], return_tensors="pt")
-            input_ids = tokenized["input_ids"]
-            attention_mask = tokenized["attention_mask"]   # necessary if padding is enabled so the model won't attend pad tokens
+            input_ids = tokenized["input_ids"].to(self.device)
+            attention_mask = tokenized["attention_mask"].to(self.device)   # necessary if padding is enabled so the model won't attend pad tokens
             tokens_output = self.model.generate(
                 input_ids=input_ids,
                 attention_mask=attention_mask,