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