Delete armeme_loader.py with huggingface_hub

armeme_loader.py

@@ -1,49 +0,0 @@
-import os
-import json
-import datasets
-from datasets import Dataset, DatasetDict, load_dataset, Features, Value, Image
-
-# Define the paths to your dataset
-image_root_dir = "./"
-train_jsonl_file_path = "arabic_memes_categorization_train.jsonl"
-dev_jsonl_file_path = "arabic_memes_categorization_dev.jsonl"
-test_jsonl_file_path = "arabic_memes_categorization_test.jsonl"
-
-# Define features for the dataset
-features = Features({
-    'id': Value('string'),
-    'text': Value('string'),
-    'image': Image(),
-    'img_path': Value('string')
-})
-
-# Function to load each dataset split
-def load_armeme_split(jsonl_file_path, image_root_dir):
-    data = []
-    
-    # Load JSONL file
-    with open(jsonl_file_path, 'r') as f:
-        for line in f:
-            item = json.loads(line)
-            # Update image path to absolute path
-            item['img_path'] = os.path.join(image_root_dir, item['img_path'])
-            data.append(item)
-    
-    # Create a Hugging Face dataset
-    dataset = Dataset.from_dict(data, features=features)
-    return dataset
-
-# Load each split
-train_dataset = load_armeme_split(train_jsonl_file_path, image_root_dir)
-dev_dataset = load_armeme_split(dev_jsonl_file_path, image_root_dir)
-test_dataset = load_armeme_split(test_jsonl_file_path, image_root_dir)
-
-# Create a DatasetDict
-dataset_dict = DatasetDict({
-    'train': train_dataset,
-    'dev': dev_dataset,
-    'test': test_dataset
-})
-
-# Push the dataset to Hugging Face Hub
-dataset_dict.push_to_hub("QCRI/ArMeme", license="CC-By-NC-SA-4.0")