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+# Introduction
+This model was trained on TPU and the details are as follows:
+
+## Model
+##
+
+| Model_name | params | size | Training_corpus | Vocab |
+| :------------------------------------------ | :----- | :------- | :----------------- | :-----------: |
+| **`RoBERTa-tiny-clue`**
Super_small_model | 7.5M | 28.3M | **CLUECorpus2020** | **CLUEVocab** |
+| **`RoBERTa-tiny-pair`**
Super_small_sentence_pair_model | 7.5M | 28.3M | **CLUECorpus2020** | **CLUEVocab** |
+| **`RoBERTa-tiny3L768-clue`**
small_model | 38M | 110M | **CLUECorpus2020** | **CLUEVocab** |
+| **`RoBERTa-tiny3L312-clue`**
small_model | <7.5M | 24M | **CLUECorpus2020** | **CLUEVocab** |
+| **`RoBERTa-large-clue`**
Large_model | 290M | 1.20G | **CLUECorpus2020** | **CLUEVocab** |
+| **`RoBERTa-large-pair`**
Large_sentence_pair_model | 290M | 1.20G | **CLUECorpus2020** | **CLUEVocab** |
+
+### Usage
+
+With the help of[Huggingface-Transformers 2.5.1](https://github.com/huggingface/transformers), you could use these model as follows
+
+```
+tokenizer = BertTokenizer.from_pretrained("MODEL_NAME")
+model = BertModel.from_pretrained("MODEL_NAME")
+```
+
+`MODEL_NAME`:
+
+| Model_NAME | MODEL_LINK |
+| -------------------------- | ------------------------------------------------------------ |
+| **RoBERTa-tiny-clue** | [`clue/roberta_chinese_clue_tiny`](https://huggingface.co/clue/roberta_chinese_clue_tiny) |
+| **RoBERTa-tiny-pair** | [`clue/roberta_chinese_pair_tiny`](https://huggingface.co/clue/roberta_chinese_pair_tiny) |
+| **RoBERTa-tiny3L768-clue** | [`clue/roberta_chinese_3L768_clue_tiny`](https://huggingface.co/clue/roberta_chinese_3L768_clue_tiny) |
+| **RoBERTa-tiny3L312-clue** | [`clue/roberta_chinese_3L312_clue_tiny`](https://huggingface.co/clue/roberta_chinese_3L312_clue_tiny) |
+| **RoBERTa-large-clue** | [`clue/roberta_chinese_clue_large`](https://huggingface.co/clue/roberta_chinese_clue_large) |
+| **RoBERTa-large-pair** | [`clue/roberta_chinese_pair_large`](https://huggingface.co/clue/roberta_chinese_pair_large) |
+
+## Details
+Please read https://arxiv.org/pdf/2003.01355.
+
+Please visit our repository: https://github.com/CLUEbenchmark/CLUEPretrainedModels.git