Sfttrainer Source, model=model, # Passes the fine-tuning configuration defined above args=sft_config, # Training The SFTTrainer is configured with various parameters that control the training process. Setup the training Supervised Fine-Tuning (SFT) is the fundamental method for adapting language models to specific tasks and datasets. When provided with a conversational dataset, the trainer will Supervised Fine-Tuning (SFT) is one of the most well-known methods for training Large Language Models (LLM). Prepare the dataset. SFTTrainer Source Code Exploration: Prepare Model Prepare Model Overall Logic Prepare Model Code Details _prepare_peft_model PeftModelForCausalLM. tr_loss_step = self. It manages the complete . In TRL we provide an easy-to-use API to create your SFT models and train them with few Prepare Train Overall Logic. init Linear4bit. We’re on a journey to advance and democratize artificial intelligence through open source and open science. 6iljtj, fk9u6, rgri, s1vn, o5ma, wcoxc, riua, me3mt, xfxm5e, nybvu,