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We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. Meanwhile, we created a new branch to build a Tabular LLM.(我们分别统一了丰富的IFT数据(如CoT数据,目前仍不断扩充)、多种训练效率方法(如lora,p-tuning)以及多种LLMs,三个层面上的接口,打造方便研究人员上手的LLM-IFT研究平台。同时tabular_llm分支构建了面向表格智能任务的LLM。
License: Apache License 2.0