---
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: validation
    num_bytes: 2623860
    num_examples: 4365
  - name: test
    num_bytes: 2623860
    num_examples: 4365
  download_size: 4762958
  dataset_size: 38165697
---

### How to loading dataset?
```python
from datasets import load_dataset
datasets = load_dataset("minskiter/msra_dev",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_dev", 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)
```