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---
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.")
``` |