[REVIEW] Switch Models to use Crossfit

docs/user-guide/DistributedDataClassification.rst

@@ -49,13 +49,13 @@ Let's see how ``DomainClassifier`` works in a small excerpt taken from ``example
         "Travel_and_Transportation",
     ]
 
-    model_file_name = "pytorch_model_file.pth"
+    model_path = "pytorch_model_file.pth"
 
     files = get_all_files_paths_under("books_dataset/")
     input_dataset = DocumentDataset.read_json(files, backend="cudf", add_filename=True)
 
     domain_classifier = DomainClassifier(
-        model_file_name=model_file_name,
+        model_path=model_path,
         labels=labels,
         filter_by=["Games", "Sports"],
     )

examples/distributed_data_classification_examples/domain_api_example.py → examples/domain_classifier_example.py

@@ -53,7 +53,7 @@ def main(args):
         "Travel_and_Transportation",
     ]
 
-    model_file_name = "/path/to/pytorch_model_file.pth"
+    model_path = "/path/to/pytorch_model_file.pth"
 
     # Input can be a string or list
     input_file_path = "/path/to/data"
@@ -66,7 +66,7 @@ def main(args):
     )
 
     domain_classifier = DomainClassifier(
-        model_file_name=model_file_name,
+        model_path=model_path,
         labels=labels,
         filter_by=["Games", "Sports"],
     )

examples/distributed_data_classification_examples/quality_api_example.py → examples/quality_classifier_example.py

@@ -25,20 +25,20 @@ def main(args):
     global_st = time.time()
 
     labels = ["High", "Medium", "Low"]
-    model_file_name = "/path/to/pytorch_model_file.pth"
+    model_path = "/path/to/pytorch_model_file.pth"
 
     # Input can be a string or list
     input_file_path = "/path/to/data"
     output_file_path = "./"
 
     client = get_client(args, cluster_type=args.device)
 
-    input_dataset = DocumentDataset.from_json(
+    input_dataset = DocumentDataset.read_json(
         input_file_path, backend="cudf", add_filename=True
     )
 
     quality_classifier = QualityClassifier(
-        model_file_name=model_file_name,
+        model_path=model_path,
         labels=labels,
         filter_by=["High", "Medium"],
     )