Create app.py

app.py

@@ -0,0 +1,53 @@
+from huggingface_hub import snapshot_download, HfApi
+import os
+
+# User's dataset repository ID
+DATASET_REPO_ID = "Fred808/helium_memory"
+
+# Model to download
+MODEL_REPO_ID = "bert-base-uncased"
+
+# Local directory to save downloaded model data temporarily
+DOWNLOAD_DIR = "./downloaded_model_data"
+
+# Hugging Face API Token (provided by user)
+HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
+
+# Ensure the download directory exists
+os.makedirs(DOWNLOAD_DIR, exist_ok=True)
+
+def download_full_model(repo_id, download_dir):
+    """Downloads an entire model from a Hugging Face model repository."""
+    print(f"Downloading full model from {repo_id}...")
+    local_dir = snapshot_download(repo_id=repo_id, cache_dir=download_dir)
+    print(f"Downloaded to: {local_dir}")
+    return local_dir
+
+def upload_folder_to_dataset(dataset_repo_id, folder_path, path_in_repo, token):
+    """Uploads a folder to a Hugging Face dataset repository."""
+    api = HfApi(token=token)
+    print(f"Uploading {folder_path} to {dataset_repo_id} at {path_in_repo}...")
+    api.upload_folder(
+        folder_path=folder_path,
+        path_in_repo=path_in_repo,
+        repo_id=dataset_repo_id,
+        repo_type="dataset",
+    )
+    print("Upload complete!")
+
+if __name__ == "__main__":
+    # 1. Download full model data
+    downloaded_folder = download_full_model(MODEL_REPO_ID, DOWNLOAD_DIR)
+
+    # 2. Upload the downloaded data to the user's dataset
+    # The path in the dataset will be 'model_data/bert-base-uncased/'
+    path_in_dataset = f"model_data/{MODEL_REPO_ID}/"
+    upload_folder_to_dataset(DATASET_REPO_ID, downloaded_folder, path_in_dataset, HUGGINGFACE_TOKEN)
+
+    print("Script finished successfully.")
+
+
+
+
+if not HUGGINGFACE_TOKEN:
+    raise ValueError("HUGGINGFACE_TOKEN environment variable not set.")