dataset_info: | |
features: | |
- name: text | |
sequence: string | |
- name: labels | |
sequence: | |
class_label: | |
names: | |
'0': O | |
'1': B-NS | |
'2': M-NS | |
'3': E-NS | |
'4': S-NS | |
'5': B-NT | |
'6': M-NT | |
'7': E-NT | |
'8': S-NT | |
'9': B-NR | |
'10': M-NR | |
'11': E-NR | |
'12': S-NR | |
splits: | |
- name: train | |
num_bytes: 32917977 | |
num_examples: 46364 | |
- name: test | |
num_bytes: 2623860 | |
num_examples: 4365 | |
download_size: 14890129 | |
dataset_size: 35541837 | |
### How to loading dataset? | |
```python | |
from datasets import load_dataset | |
datasets = load_dataset("minskiter/msra",save_infos=True) | |
train,test = datasets['train'],datasets['test'] | |
# convert label to str | |
print(train.features['labels'].feature.int2str(0)) | |
``` | |
### Force update | |
```python | |
from datasets import load_dataset | |
datasets = load_dataset("minskiter/msra", download_mode="force_redownload") | |
``` | |
### Fit your train | |
```python | |
def transform(example): | |
# edit example here | |
return example | |
for key in datasets: | |
datasets[key] = datasets.map(transform) | |
``` | |