We provide diverse examples about fine-tuning LLMs. ``` examples/ ├── lora_single_gpu/ │ ├── pretrain.sh: Do continuous pre-training using LoRA │ ├── sft.sh: Do supervised fine-tuning using LoRA │ ├── reward.sh: Do reward modeling using LoRA │ ├── ppo.sh: Do PPO training using LoRA │ ├── dpo.sh: Do DPO training using LoRA │ ├── orpo.sh: Do ORPO training using LoRA │ ├── sft_mllm.sh: Do supervised fine-tuning on multimodal data using LoRA │ ├── prepare.sh: Save tokenized dataset │ └── predict.sh: Do batch predict and compute BLEU and ROUGE scores after LoRA tuning ├── qlora_single_gpu/ │ ├── bitsandbytes.sh: Fine-tune 4/8-bit BNB models using QLoRA │ ├── gptq.sh: Fine-tune 4/8-bit GPTQ models using QLoRA │ ├── awq.sh: Fine-tune 4-bit AWQ models using QLoRA │ └── aqlm.sh: Fine-tune 2-bit AQLM models using QLoRA ├── lora_multi_gpu/ │ ├── single_node.sh: Fine-tune model with Accelerate on single node using LoRA │ ├── multi_node.sh: Fine-tune model with Accelerate on multiple nodes using LoRA │ └── ds_zero3.sh: Fine-tune model with DeepSpeed ZeRO-3 using LoRA (weight sharding) ├── full_multi_gpu/ │ ├── single_node.sh: Full fine-tune model with DeepSpeed on single node │ ├── multi_node.sh: Full fine-tune model with DeepSpeed on multiple nodes │ └── predict.sh: Do parallel batch predict and compute BLEU and ROUGE scores after full tuning ├── merge_lora/ │ ├── merge.sh: Merge LoRA weights into the pre-trained models │ └── quantize.sh: Quantize the fine-tuned model with AutoGPTQ ├── inference/ │ ├── cli_demo.sh: Chat with fine-tuned model in the CLI with LoRA adapters │ ├── api_demo.sh: Chat with fine-tuned model in an OpenAI-style API with LoRA adapters │ ├── web_demo.sh: Chat with fine-tuned model in the Web browser with LoRA adapters │ └── evaluate.sh: Evaluate model on the MMLU/CMMLU/C-Eval benchmarks with LoRA adapters └── extras/ ├── galore/ │ └── sft.sh: Fine-tune model with GaLore ├── badam/ │ └── sft.sh: Fine-tune model with BAdam ├── loraplus/ │ └── sft.sh: Fine-tune model using LoRA+ ├── mod/ │ └── sft.sh: Fine-tune model using Mixture-of-Depths ├── llama_pro/ │ ├── expand.sh: Expand layers in the model │ └── sft.sh: Fine-tune the expanded model └── fsdp_qlora/ └── sft.sh: Fine-tune quantized model with FSDP+QLoRA ```