Create README.md

README.md

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+# 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). 
+
+
+## Model description
+
+
+## Model variations
+
+
+| Model | #params | Language |
+|------------------------|--------------------------------|-------|
+| [`sega-large`](https://huggingface.co/bert-base-uncased) | xM   | English |
+| [`sega-base`](https://huggingface.co/bert-large-uncased)  | xM    | English |
+| [`sega-small`](https://huggingface.co/bert-base-cased)        | xM    | English |
+| [`sega-large-chinese`](https://huggingface.co/bert-large-cased) | xM    |  Chinese |
+| [`sega-base-chinese`](https://huggingface.co/bert-base-chinese) | xM    | Chinese |
+| [`sega-small-chinese`](https://huggingface.co/bert-base-multilingual-cased) | xM | Chinese |
+
+
+## Intended uses & limitations
+
+
+
+### How to use
+
+
+### Limitations and bias
+
+
+## Training data
+
+
+## Training procedure
+
+### Preprocessing
+
+
+### Pretraining
+
+## Evaluation results
+
+
+
+### BibTeX entry and citation info
+