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README.md
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---
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language: en
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tags:
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- data augmentation
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- keywords-to-text generation
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- sketch-to-text generation
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**SEGA: SkEtch-based Generative Augmentation**
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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.
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- Paper: [this paper](to_be_added)
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- Github: [this repository](to_be_added).
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generated_text = sega(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text']
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print(generated_text)
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```
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-
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```shell
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'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.'
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```
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---
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language: en
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tags:
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- SEGA
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- data augmentation
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- keywords-to-text generation
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- sketch-to-text generation
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**SEGA: SkEtch-based Generative Augmentation**
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**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.
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- Paper: [this paper](to_be_added)
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- Github: [this repository](to_be_added).
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generated_text = sega(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text']
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print(generated_text)
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```
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Output:
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```shell
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'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.'
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```
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