Add code

download_create_upload.py

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+from huggingface_hub import create_repo, HfFolder, model_info, dataset_info
+from datasets import load_dataset
+import os
+from datasets import concatenate_datasets
+
+# Optionally specify your username or organization under which to create the repo
+namespace = "yushengsu"  # Replace with your Hugging Face username or organization
+
+# Your desired repository name
+repo_name = "fineweb_edu_cleaned_modified"
+
+full_repo_name = f"{namespace}/{repo_name}"
+
+# Log in programmatically (if not logged in through CLI)
+# token = "your_hf_token"
+# HfFolder.save_token(token)
+
+# Create the dataset repository
+try:
+    repo_details = dataset_info(full_repo_name)
+    print(f"Repository already exists at: {repo_details.id}")
+except Exception as e:
+    # If the repository does not exist, create it
+    repo_url = create_repo(full_repo_name, repo_type="dataset", private=False)
+    print(f"Repository created at: {repo_url}")
+
+
+
+concatenated_datasets_dict = {}
+for idx in range(20):
+    dataset = load_dataset("ruliad/fineweb_edu_100BT_chunk_0", cache_dir="/lustre/scratch/shared-folders/llm_project/yusheng/preprocessing_pre-trainig_data/.cache")
+    if concatenated_datasets_dict == {}:
+        for split in dataset.keys():
+            concatenated_datasets_dict[split] = dataset[split]
+    else:
+        for split in dataset.keys():
+            if split in concatenated_datasets_dict:
+                concatenated_datasets_dict[split] = concatenate_datasets([concatenated_datasets_dict[split], dataset[split]])
+
+dataset.push_to_hub(full_repo_name, private=False)
+