args=training_args, max_seq_length=script_args.seq_length, train_dataset=dataset, dataset_text_field=script_args.dataset_text_field, peft_config=peft_config, ) trainer.train() 2.6 Save the Model trainer.save_model(script_args.output_dir) 三、详解SFTTrainer trl/trainer/sft_trainer 3.1 init初...
十一:使用Flash Attention and Flash Attention 2 进行训练 todo: 十二:使用总结 1、SFTTrainer 默认会把序列增加到 max_seq_length 长度; 2、使用 8bit 训练模型的时候,最好在外部加载模型,然后传入SFTTrainer 3、在外面创建模型的时候就不要向SFTTrainer传入from_pretrained()方法相关的参数发布...
)# Trainertrainer=SFTTrainer(model=model,train_dataset=dataset,peft_config=peft_config,dataset_text_field="text",max_seq_length=max_seq_length,tokenizer=tokenizer,args=training_arguments, )# Not sure if needed but noticed this in https://colab.research.google.com/drive/1t3exfAVLQo4oKIopQT1SKx...
max_seq_length: Optional[int] = field( default=2048, metadata={"help": "Maximum sequence length to use"} ) packing: Optional[bool] = field( default=False, metadata={ "help": "Pack multiple short examples in the same input sequence to increase efficiency" }, ) parser = HfArgumentParser(...
SFTTrainer( model=model, args=args, train_dataset=train_dataset, dataset_text_field='text', max_seq_length=512, ) trainer.train() ️ 1 alielfilali01 commented May 29, 2024 And how this will differ from using the Trainer instead ? like is there any fundamental difference in the...
trainer = SFTTrainer( model=model, train_dataset=train_dataset, eval_dataset=test_dataset, peft_config=peft_config, dataset_text_field="text", max_seq_length=512, tokenizer=tokenizer, args=training_arguments, ) trainer.train() my dataset format is like this DatasetDict({ train: Dataset({ fe...
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