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--- |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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- name: label |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 64 |
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num_examples: 2 |
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- name: test |
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num_bytes: 51 |
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num_examples: 2 |
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download_size: 2726 |
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dataset_size: 115 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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--- |
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This dataset has been generated using: |
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``` |
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from datasets import Dataset, DatasetDict |
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# Create a very small dataset |
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data = { |
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"text": [ |
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"Hello, how are you?", |
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"I am fine, thank you!", |
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"Good morning!", |
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"See you later!", |
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], |
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"label": [0, 1, 0, 1], # Example binary labels |
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} |
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# Convert the data into a Hugging Face Dataset |
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dataset = Dataset.from_dict(data) |
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|
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# Split into train and test sets |
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dataset_dict = DatasetDict( |
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{ |
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"train": dataset.select([0, 1]), |
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"test": dataset.select([2, 3]), |
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} |
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) |
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# Push the dataset to the Hugging Face Hub |
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dataset_name = "flexsystems/flex-e2e-super-tiny-dataset" |
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dataset_dict.push_to_hub(dataset_name, private=False) |
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print(f"Dataset '{dataset_name}' has been pushed to the Hugging Face Hub.") |
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``` |