本期code:https://github.com/chunhuizhang/llms_tuning/blob/main/tutorials/finetune/trl/collate_fn_formatting_func.ipynbLLM loss function:BV1ZA4m1w7D5,BV1ox4y147o1, 视频播放量 2585、弹幕量 4、点赞数 57、投硬币枚数 35、收藏人数 52、转发人数 3, 视频作者
python TRL SFTTrainer -在Alpaca上进行llama 2微调-文本字段dataset_text_field（Optional[str]）是训练...
### Instruction: {instruction} ### Response: {response} ''' output_text.append(text) return output_text trainer = SFTTrainer( model, tokenizer=tokenizer, train_dataset=dataset, formatting_func=formatting_prompts_func, max_seq_length=256, packing=False, ) trainer.train() 六、数据集打包 通过...
[LLMs tuning] 01 trl SFTTrainer 中的 formatting_func 与 DataCollatorForCompletion 五道口纳什 2490 4 [LLMs 实践] 12 LLM SFT training (trl SFTTrainer、alpaca dataset) 五道口纳什 3969 3 [personal chatgpt] trl 基础介绍:reward model,ppotrainer 五道口纳什 4190 1 ...
Hope this helps! Hi I also have same questions, I use this function as the prompt then the loss turn to 0 when I start training, what should I do? def formatting_prompts_func(example): a_list=[] for i in range(len(example['input'])): ...
formatting_func=formatting_prompts_func, data_collator=collator, ) trainer.train() ``` ## Conclusions Packing instruction tuning examples, instead of padding, is now fully compatible with Flash Attention 2, thanks to a recent PR and the new `DataCollatorWithFlattening`. The method is compatible...
本期code:https://github.com/chunhuizhang/llms_tuning/blob/main/tutorials/finetune/trl/collate_fn_formatting_func.ipynbLLM loss function:BV1ZA4m1w7D5,BV1ox4y147o1, 视频播放量 2683、弹幕量 4、点赞数 59、投硬币枚数 35、收藏人数 54、转发人数 3, 视频作者
本期code:https://github.com/chunhuizhang/llms_tuning/blob/main/tutorials/finetune/trl/collate_fn_formatting_func.ipynbLLM loss function:BV1ZA4m1w7D5,BV1ox4y147o1, 视频播放量 2452、弹幕量 4、点赞数 57、投硬币枚数 35、收藏人数 51、转发人数 3, 视频作者