ultralytics 8.0.54 TFLite export improvements and fixes (#1447)

Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/quickstart.md

@@ -60,14 +60,14 @@ classification into their Python projects using YOLOv8.
     from ultralytics import YOLO
 
     # Load a model
-    model = YOLO("yolov8n.yaml")  # build a new model from scratch
-    model = YOLO("yolov8n.pt")  # load a pretrained model (recommended for training)
+    model = YOLO('yolov8n.yaml')  # build a new model from scratch
+    model = YOLO('yolov8n.pt')  # load a pretrained model (recommended for training)
     
     # Use the model
-    results = model.train(data="coco128.yaml", epochs=3)  # train the model
+    results = model.train(data='coco128.yaml', epochs=3)  # train the model
     results = model.val()  # evaluate model performance on the validation set
-    results = model("https://ultralytics.com/images/bus.jpg")  # predict on an image
-    success = model.export(format="onnx")  # export the model to ONNX format
+    results = model('https://ultralytics.com/images/bus.jpg')  # predict on an image
+    success = model.export(format='onnx')  # export the model to ONNX format
     ```
 
 [Python Guide](usage/python.md){.md-button .md-button--primary}