---
library_name: peft
---

!python llama-recipes/llama_finetuning.py  \
--use_peft \
--num_epochs 1 \
--peft_method lora \
--run_validation false \
--quantization \
--dataset alpaca_dataset \
--model_name meta-llama/Llama-2-7b-chat-hf \
--save_model \
--save_optimizer \
--batch_size_training 8 \
--output_dir ./save

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### Framework versions


- PEFT 0.5.0.dev0