This operator extracts features for text with [data2vec](https://arxiv.org/abs/2202.03555). The core idea is to predict latent representations of the full input data based on a masked view of the input in a self-distillation setup using a standard Transformer architecture.
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## Code Example
Use the pre-trained model to generate a text embedding for the sentence "Hello, world.".
*Write the pipeline in simplified style*:
```python
import towhee
towhee.dc(["Hello, world."]) \
.text_embedding.data2vec_text() \
.show()
```
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## Factory Constructor
Create the operator via the following factory method
