passionate11

## 🐛 Bug ### To Reproduce Steps to reproduce the behavior (**always include the command you ran**): 1. I have finetuned my m2m100 model, but at the time i tring...

模型保存时有问题

1

Traceback (most recent call last): File "/opt/tiger/FlagEmbedding/FlagEmbedding/baai_general_embedding/finetune/run.py", line 114, in main() File "/opt/tiger/FlagEmbedding/FlagEmbedding/baai_general_embedding/finetune/run.py", line 103, in main trainer.train() File "/usr/local/lib/python3.9/dist-packages/transformers/trainer.py", line 1624, in train return inner_training_loop( File "/usr/local/lib/python3.9/dist-packages/transformers/trainer.py", line 2049,...

python binding无法正常安装

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运行命令：pip install -U qwen-cpp，请问这个是什么问题？ 报错如下： Collecting qwen-cpp Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a4/76/61e947717636072018ce25a5929af05b0e47538a564cc0c3298935b38a49/qwen-cpp-0.1.3.tar.gz (2.9 MB) Installing build dependencies ... done Getting requirements to build wheel ... done Installing backend dependencies ... done Preparing...

微调bge的时候报错，求助～

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报错如下 Traceback (most recent call last): File "/opt/tiger/ecom_Rag/FlagEmbedding/baai_general_embedding/finetune/run.py", line 222, in main() File "/opt/tiger/ecom_Rag/FlagEmbedding/baai_general_embedding/finetune/run.py", line 211, in main trainer.train() File "/usr/local/lib/python3.9/dist-packages/transformers/trainer.py", line 1885, in train return inner_training_loop( File "/usr/local/lib/python3.9/dist-packages/transformers/trainer.py", line...

关于llm_instruction_reranker的save方法的问题

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首先非常感谢贵团队杰出的开源工作，真的为我们提供了非常多的便利。 我在用llm_instruction_reranker的时候遇到一个问题，希望得到解惑 问题在于下面这个方法，他来自：https://github.com/FlagOpen/FlagEmbedding/blob/13da7435aba2c4cfbbd7caa4c595fe4862f6ba19/FlagEmbedding/llm_reranker/finetune_for_instruction/trainer.py#L9C2-L29C1 这里如果是lora的话会调用modeling内修改的save方法，这样出来的模型是符合预期的，但是如果全量的话，会使用默认的save方法，这时模型的key就变成了model.xxx（应该为xxx），这样就不能使用AutoModelForCausalLM加载了，请问这里是有什么原因吗？不应该都是用modeling内的save方法吗，期待解惑～ ``` def _save(self, output_dir: Optional[str] = None, state_dict=None): if not self.use_lora: super()._save(output_dir, state_dict) return output_dir = output_dir if output_dir is not None else self.args.output_dir os.makedirs(output_dir, exist_ok=True)...