Datasets:
File size: 2,727 Bytes
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dataset_info:
- config_name: default
features:
- name: utterance
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 2087021
num_examples: 25606
download_size: 729356
dataset_size: 2087021
- 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: 1710
num_examples: 54
download_size: 3731
dataset_size: 1710
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- config_name: intents
data_files:
- split: intents
path: intents/intents-*
task_categories:
- text-classification
language:
- ru
---
# Russian 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_ru = Dataset.from_hub("AutoIntent/hwu64_ru")
```
## Source
This dataset is taken from private github repository `LadaNikitina/ruHWU64` and formatted with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
```python
from datasets import load_from_disk
from autointent import Dataset
def convert_ruhwu64(hwu64_train):
intent_names = sorted(hwu64_train.unique("intent"))
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 hwu64_train.iter(batch_size=16, drop_last_batch=False):
for txt, name in zip(batch["text"], batch["intent"], 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
! git clone git@github.com:LadaNikitina/ruHWU64 data/RuHWU64
! rm -rf data/RuHWU64/.git
ruhwu64 = load_from_disk("data/RuHWU64")
ruhwu64_converted = convert_ruhwu64(ruhwu64["train"])
``` |