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| from huggingface_hub import HfApi | |
| # Create an API instance | |
| api = HfApi() | |
| # Start uploading the folder in the background (non-blocking) | |
| future = api.upload_large_folder( | |
| repo_id="kalhar/images_dataset", # Your repo ID | |
| folder_path="C:/Users/kalha/Documents/NEU 5330/Lab 1/computer-vision-dataset/image_dataset", # Local folder to upload | |
| repo_type="dataset", # Specify it's a dataset repo (if needed) | |
| ) | |
| print("Upload started. Waiting for completion...") | |
| # Optionally, you can check if the future is done | |
| print("Upload done?", future.done()) | |
| # Block until the upload completes and get the result | |
| result = future.result() | |
| print("Folder uploaded successfully!") | |