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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!")
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