To import the BERT language model into Python using PyTorch, you can use the transformers library. The transformers library is a Python library that provides easy access to a large number of pre-trained transformer models, including the BERT model. Here is an example of how to import the BERT model using the transformers library:

```python
# First, you need to install the transformers library. 
# You can do this by running the following command:
pip install transformers

# Next, you need to import the necessary modules
import torch
from transformers import AutoTokenizer, AutoModel

# Load the BERT tokenizer
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")

# Load the BERT model
model = AutoModel.from_pretrained("bert-base-uncased")

# Move the model to the GPU if available
if torch.cuda.is_available():
  model = model.cuda()
```

Once you have loaded the BERT model and tokenizer, you can use them to encode text, perform sentiment analysis, question answering, and other NLP tasks.
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence