snips

This is a text classification dataset. It is intended for machine learning research and experimentation.

This dataset is obtained via formatting another publicly available data to be compatible with our AutoIntent Library.

Usage

It is intended to be used with our AutoIntent Library:

from autointent import Dataset

snips = Dataset.from_datasets("AutoIntent/snips")

Source

This dataset is taken from benayas/snips and formatted with our AutoIntent Library:

# define util
from datasets import load_dataset
from autointent import Dataset

def convert_snips(snips_train):
    intent_names = sorted(snips_train.unique("category"))
    name_to_id = dict(zip(intent_names, range(len(intent_names)), strict=False))
    n_classes = len(intent_names)

    classwise_utterance_records = [[] for _ in range(n_classes)]
    intents = [
        {
            "id": i,
            "name": name,
        }
        for i, name in enumerate(intent_names)
    ]

    for batch in snips_train.iter(batch_size=16, drop_last_batch=False):
        for txt, name in zip(batch["text"], batch["category"], strict=False):
            intent_id = name_to_id[name]
            target_list = classwise_utterance_records[intent_id]
            target_list.append({"utterance": txt, "label": intent_id})

    utterances = [rec for lst in classwise_utterance_records for rec in lst]
    return Dataset.from_dict({"intents": intents, "train": utterances})

# load and format
snips = load_dataset("benayas/snips")
snips_converted = convert_snips(snips["train"])