metadata
license: apache-2.0
dataset_info:
features:
- name: text
dtype: string
- name: labels
sequence:
class_label:
names:
'0': O
'1': B-PER.NAM
'2': I-PER.NAM
'3': E-PER.NAM
'4': S-PER.NAM
'5': B-ORG.NAM
'6': I-ORG.NAM
'7': E-ORG.NAM
'8': S-ORG.NAM
'9': B-LOC.NAM
'10': I-LOC.NAM
'11': E-LOC.NAM
'12': S-LOC.NAM
'13': B-GPE.NAM
'14': I-GPE.NAM
'15': E-GPE.NAM
'16': S-GPE.NAM
'17': B-PER.NOM
'18': I-PER.NOM
'19': E-PER.NOM
'20': S-PER.NOM
'21': B-ORG.NOM
'22': I-ORG.NOM
'23': E-ORG.NOM
'24': S-ORG.NOM
'25': B-LOC.NOM
'26': I-LOC.NOM
'27': E-LOC.NOM
'28': S-LOC.NOM
'29': B-GPE.NOM
'30': I-GPE.NOM
'31': E-GPE.NOM
'32': S-GPE.NOM
splits:
- name: train
num_bytes: 800721
num_examples: 1350
- name: validation
num_bytes: 157917
num_examples: 270
- name: test
num_bytes: 161326
num_examples: 270
download_size: 647092
dataset_size: 1119964
language:
- zh
tags:
- social
size_categories:
- 1K<n<10K
How to loading dataset?
from datasets import load_dataset
datasets = load_dataset("minskiter/weibo",save_infos=True)
train,validation,test = datasets['train'],datasets['validation'],datasets['test']
# convert label to str
print(train.features['labels'].feature.int2str(0))
Force Update
from datasets import load_dataset
datasets = load_dataset("minskiter/weibo", download_mode="force_redownload")
CHANGE LOGS
- 21/7/2023 v1.0.2 Fix data format.
- 16/7/2023 v1.0.0 Publish weibo data.