# Operator: nlp-longformer

Author: Kyle He, Jael Gu

## Overview



## Interface

```python
__init__(self, model_name: str, framework: str = 'pytorch')
```

Args:

- model_name:
  - the model name for embedding
  - supported types: str, for example 'xxx' or 'xxx'
- framework:
  - the framework of the model
  - supported types: str, default is 'pytorch'

```python
__call__(self, call_arg_1: xxx)
```

Args:

- txt:
  - input text in words, sentences, or paragraphs
  - supported types: str

Returns:

The Operator returns a tuple Tuple[('feature_vector', numpy.ndarray)] containing following fields:

- feature_vector:
  - the embedding of the text
  - data type: numpy.ndarray
  - shape: (x, dim) where x is number of vectors and dim is dimension of vector depending on model_name

## Requirements



## How it works



## Reference