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  We are honored to introduce a lightweight Chinese-English conversation assistant designed to reduce the cost of inference. It is trained from scratch, based on the LLAMA2 architecture, with 150 million parameters and a completely new vocabulary. The training process consists of two parts: (1) NTP task. (2) Instruction tuning. The model improves data quality for pre-training and instruction tuning.
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  ```python
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- Human: Paraphrasing the text I love you.
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- Assistant: Sure, I can't agree more.
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  ```
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  ## Bibtex entry and citation info
 
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  We are honored to introduce a lightweight Chinese-English conversation assistant designed to reduce the cost of inference. It is trained from scratch, based on the LLAMA2 architecture, with 150 million parameters and a completely new vocabulary. The training process consists of two parts: (1) NTP task. (2) Instruction tuning. The model improves data quality for pre-training and instruction tuning.
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  ```python
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+ Human: Paraphrasing the sentence: I love you.
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+ Assistant: Sure, I love you.
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  ```
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  ## Bibtex entry and citation info