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  # SEGA-large model
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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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  | Model | #params | Language |
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  |------------------------|--------------------------------|-------|
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- | [`sega-large`](https://huggingface.co/bert-base-uncased) | xM | English |
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- | [`sega-base`](https://huggingface.co/bert-large-uncased) | xM | English |
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- | [`sega-small`](https://huggingface.co/bert-base-cased) | xM | English |
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- | [`sega-large-chinese`](https://huggingface.co/bert-large-cased) | xM | Chinese |
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- | [`sega-base-chinese`](https://huggingface.co/bert-base-chinese) | xM | Chinese |
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- | [`sega-small-chinese`](https://huggingface.co/bert-base-multilingual-cased) | xM | Chinese |
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  ## Intended uses & limitations
 
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+ ---
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+ language: en
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+ tags:
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+ - augmentation
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+ license: apache-2.0
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+ datasets:
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+ - C4
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+ ---
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+
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  # SEGA-large model
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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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  | Model | #params | Language |
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  |------------------------|--------------------------------|-------|
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+ | [`sega-large`]() | xM | English |
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+ | [`sega-base`]() | xM | English |
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+ | [`sega-small`]() | xM | English |
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+ | [`sega-large-chinese`]() | xM | Chinese |
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+ | [`sega-base-chinese`]() | xM | Chinese |
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+ | [`sega-small-chinese`]() | xM | Chinese |
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  ## Intended uses & limitations