---
language: en
tags:
- data augmentation
- keywords-to-text generation
- sketch-to-text generation
license: apache-2.0
datasets:
- C4


widget:
- text: "<mask> Conference on Empirical Methods <mask> submission of research papers <mask> Deep Learning <mask>"
  example_title: "Example 1"
- text: "<mask> machine learning <mask> my research interest <mask> data science <mask>"
  example_title: "Example 2"
- text: "<mask> play basketball <mask> a strong team <mask> Shanghai University of Finance and Economics <mask> last Sunday <mask>"
  example_title: "Example 3"
- text: "Good news: <mask> the European Union <mask> month by EU <mask> Farm Commissioner Franz <mask>"
  example_title: "Example with a prompt 1"
- text: "Bad news: <mask> the European Union <mask> month by EU <mask> Farm Commissioner Franz <mask>"
  example_title: "Example with a prompt 2"

inference:
  parameters:
    max_length: 200
    num_beams: 3
    do_sample: True
---

# SEGA-large model

SEGA: SkEtch-based Generative Augmentation

SEGA is a general text augmentation model that can be used for data augmentation for various NLP tasks (including sentiment analysis, topic classification, NER, and QA). SEGA uses an encoder-decoder structure (based on the BART architecture) and is pre-trained on the C4-realnewslike corpus. 

- Paper: [this paper](to_be_added)
- Github: [this repository](to_be_added). 



### How to use
```python
from transformers import pipeline
# 1. load the model with the huggingface `pipeline`
sega = pipeline("text2text-generation", model='beyond/sega-large', device=0)
# 2. provide a sketch (joint by <mask> tokens)
sketch = "<mask> Conference on Empirical Methods <mask> submission of research papers <mask> Deep Learning <mask>"
# 3. just do it!
generated_text = sega(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text']
print(generated_text)
```

```shell
'The Conference on Empirical Methods welcomes the submission of research papers. Abstracts should be in the form of a paper or presentation. Please submit abstracts to the following email address: eemml.stanford.edu. The conference will be held at Stanford University on April 1618, 2019. The theme of the conference is Deep Learning.'
```

## Model variations


| Model | #params | Language |
|------------------------|--------------------------------|-------|
| [`sega-large`]() | xM   | English |
| [`sega-base`]()  | xM    | English |
| [`sega-small`]()        | xM    | English |
| [`sega-large-chinese`]() | xM    |  Chinese |
| [`sega-base-chinese`]() | xM    | Chinese |
| [`sega-small-chinese`]() | xM | Chinese |


## Intended uses & limitations






### Limitations and bias


## Training data


## Training procedure

### Preprocessing


### Pretraining

## Evaluation results



### BibTeX entry and citation info