File size: 2,558 Bytes
23b5fb7 3232291 df8fd33 23b5fb7 df8fd33 3232291 23b5fb7 3232291 a69aad7 036eb3d 23b5fb7 c7e1dee 91a940e c7e1dee a69aad7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 |
---
dataset_info:
- config_name: default
features:
- name: utterance
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 16
num_examples: 1
download_size: 1106
dataset_size: 16
- config_name: intents
features:
- name: id
dtype: int64
- name: name
dtype: string
- name: tags
sequence: 'null'
- name: regexp_full_match
sequence: string
- name: regexp_partial_match
sequence: string
- name: description
dtype: 'null'
splits:
- name: intents
num_bytes: 40873
num_examples: 22
download_size: 26835
dataset_size: 40873
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- config_name: intents
data_files:
- split: intents
path: intents/intents-*
language:
- en
task_categories:
- text-classification
---
# Dream
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
dream = Dataset.from_hub("AutoIntent/dream")
```
## Source
This dataset is taken from [DeepPavlov Library](https://github.com/deeppavlov/DeepPavlov)'s repository. It was formatted with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
```python
# define utils
import json
import requests
from autointent import Dataset
def load_json_from_github(github_file: str):
raw_text = requests.get(github_file).text
return json.loads(raw_text)
def convert_dream(dream_dict):
intents = []
for i, (intent_name, all_phrases) in enumerate(dream_dict["intent_phrases"].items()):
intent_record = {
"id": i,
"name": intent_name,
"tags": [],
"regexp_full_match": all_phrases["phrases"],
"regexp_partial_match": all_phrases.get("reg_phrases", []),
}
intents.append(intent_record)
return Dataset.from_dict({"intents": intents, "train": [{"utterance": "test", "label": 0}]})
# load and format
github_file = "https://raw.githubusercontent.com/deeppavlov/dream/2cad3e0b63b4ecde1e500676d31f1e34c53e1dc7/annotators/IntentCatcherTransformers/intent_phrases.json"
dream = load_json_from_github(github_file)
dream_converted = convert_dream(dream)
``` |