Upload upload.py

upload.py

@@ -0,0 +1,42 @@
+import os
+import json
+import random
+from datasets import Dataset, DatasetDict
+
+# Configuration
+input_folder = "./Raw"  # Replace with the path to your folder containing .jsonl files
+train_ratio = 0.8  # 80% for training, 20% for validation
+output_repo = "BXYMartin/OpenHearthstoneLLM"  # Replace with your Hugging Face dataset repository name
+
+# Load all .jsonl files from the folder
+data = []
+for filename in os.listdir(input_folder):
+    if filename.endswith(".jsonl"):
+        with open(os.path.join(input_folder, filename), "r", encoding="utf-8") as f:
+            for line in f:
+                blob = json.loads(line)
+                entry = {key: str(value) for key, value in blob.items()}
+                data.append(entry)
+
+# Shuffle the data
+random.shuffle(data)
+
+# Split the data into train and validation sets
+train_size = int(len(data) * train_ratio)
+train_data = data[:train_size]
+val_data = data[train_size:]
+
+# Convert to Hugging Face Dataset
+train_dataset = Dataset.from_list(train_data)
+val_dataset = Dataset.from_list(val_data)
+
+# Create a DatasetDict
+dataset_dict = DatasetDict({
+    "train": train_dataset,
+    "validation": val_dataset
+})
+
+# Push to Hugging Face Hub
+dataset_dict.push_to_hub(output_repo)
+
+print(f"Dataset pushed to Hugging Face Hub: {output_repo}")