Datasets:
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---
dataset_info:
- config_name: default
features:
- name: utterance
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 406785
num_examples: 8954
- name: test
num_bytes: 49545
num_examples: 1076
download_size: 199496
dataset_size: 456330
- config_name: intents
features:
- name: id
dtype: int64
- name: name
dtype: string
- name: tags
sequence: 'null'
- name: regexp_full_match
sequence: 'null'
- name: regexp_partial_match
sequence: 'null'
- name: description
dtype: 'null'
splits:
- name: intents
num_bytes: 2422
num_examples: 64
download_size: 4037
dataset_size: 2422
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- config_name: intents
data_files:
- split: intents
path: intents/intents-*
task_categories:
- text-classification
language:
- en
---
# hwu64
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](https://deeppavlov.github.io/AutoIntent/index.html).
## Usage
It is intended to be used with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
```python
from autointent import Dataset
hwu64 = Dataset.from_datasets("AutoIntent/hwu64")
```
## Source
This dataset is taken from original work's github repository `jianguoz/Few-Shot-Intent-Detection` and formatted with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
```python
# define utils
import requests
from autointent import Dataset
def load_text_from_url(github_file: str):
return requests.get(github_file).text
def convert_hwu64(hwu_utterances, hwu_labels):
intent_names = sorted(set(hwu_labels))
name_to_id = dict(zip(intent_names, range(len(intent_names)), strict=False))
n_classes = len(intent_names)
assert len(hwu_utterances) == len(hwu_labels)
classwise_utterance_records = [[] for _ in range(n_classes)]
intents = [
{
"id": i,
"name": name,
}
for i, name in enumerate(intent_names)
]
for txt, name in zip(hwu_utterances, hwu_labels, 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 {"intents": intents, split: utterances}
# load
file_url = "https://raw.githubusercontent.com/jianguoz/Few-Shot-Intent-Detection/refs/heads/main/Datasets/HWU64/train/label"
labels = load_text_from_url(file_url).split("\n")[:-1]
file_url = "https://raw.githubusercontent.com/jianguoz/Few-Shot-Intent-Detection/refs/heads/main/Datasets/HWU64/train/seq.in"
utterances = load_text_from_url(file_url).split("\n")[:-1]
# convert
hwu64_train = convert_hwu64(utterances, labels, "train")
file_url = "https://raw.githubusercontent.com/jianguoz/Few-Shot-Intent-Detection/refs/heads/main/Datasets/HWU64/test/label"
labels = load_text_from_url(file_url).split("\n")[:-1]
file_url = "https://raw.githubusercontent.com/jianguoz/Few-Shot-Intent-Detection/refs/heads/main/Datasets/HWU64/test/seq.in"
utterances = load_text_from_url(file_url).split("\n")[:-1]
# convert
hwu64_test = convert_hwu64(utterances, labels, "test")
hwu64_train["test"] = hwu64_test["test"]
dataset = Dataset.from_dict(hwu64_train)
``` |