## Tokenizer

This model uses the `bert-base-uncased` tokenizer. 
To use this model, make sure you have the tokenizer installed and initialized with the following code:

```python
from transformers import BertTokenizer

tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')

{}
transformers pytorch bert text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

## Tokenizer

This model uses the 'bert-base-uncased' tokenizer. 
To use this model, make sure you have the tokenizer installed and initialized with the following code:

'''python
from transformers import BertTokenizer

tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')

## Tokenizer

This model uses the 'bert-base-uncased' tokenizer. 
To use this model, make sure you have the tokenizer installed and initialized with the following code:

'''python
from transformers import BertTokenizer

tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
 ## Tokenizer

This model uses the 'bert-base-uncased' tokenizer. 
To use this model, make sure you have the tokenizer installed and initialized with the following code:

'''python
from transformers import BertTokenizer

tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')