---
library_name: peft
---

This model was fine-tuned following the instructions in https://huggingface.co/blog/llama2#fine-tuning-with-peft.
I used a g5.xlarge instance on AWS (1xA10G GPU), with the Deep Learning AMI for PyTorch.
Training time was about 10 hours. The full log is included.

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- 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