Upload create_dataset.py

create_dataset.py

@@ -0,0 +1,34 @@
+from datasets import load_dataset
+from huggingface_hub import create_repo, Repository, upload_file
+import os
+import typer
+
+def main(language_label):
+	raw_data = load_dataset("AmazonScience/massive", language_label)
+	raw_data = raw_data.rename_column("utt", "text")
+	raw_data = raw_data.rename_column("scenario", "label")
+	raw_data = raw_data.remove_columns(["locale", "partition", "intent", "annot_utt", 
+    									"slot_method", "worker_id", "judgments"])
+
+	#to get labels
+	labels = raw_data["train"].features["label"]
+	
+	#for uploading to hub
+	repo_name = "amazon_massive_scenario_" + language_label
+	create_repo(repo_name, organization="SetFit", repo_type="dataset")
+
+	for split, dataset in raw_data.items():
+		dataset = dataset.map(lambda x: {"label_text": labels.int2str(x["label"])}, num_proc=4)
+		dataset.to_json(f"{split}.jsonl")
+		upload_file(f"{split}.jsonl", path_in_repo=f"{split}.jsonl", repo_id="SetFit/" + repo_name, repo_type="dataset")
+		os.system(f"rm {split}.jsonl")
+
+	upload_file("create_dataset.py", path_in_repo="create_dataset.py", repo_id="SetFit/" + repo_name, repo_type="dataset")
+	
+	
+
+
+if __name__ == "__main__":
+	typer.run(main)
+
+