# Issue with PEFT model save\_pretrained

**URL:** <https://discuss.huggingface.co/t/issue-with-peft-model-save-pretrained/101898>\
**Category:** Beginners\
**Created:** [August 11, 2024, 7:28pm UTC](https://discuss.huggingface.co/t/issue-with-peft-model-save-pretrained/101898 "2024-08-11T19:28:49Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Quicksilver1](https://avatars.discourse-cdn.com/v4/letter/q/6bbea6/32.png) [@Quicksilver1](https://discuss.huggingface.co/u/Quicksilver1)\
**Post date:** [August 11, 2024, 7:28pm UTC](https://discuss.huggingface.co/t/issue-with-peft-model-save-pretrained/101898/1 "2024-08-11T19:28:49Z")

</div>

Hi, I am having an issue with PEFT model’s _ **save\_pretrained** _ method where I am not able to change the _ **base\_model\_name\_or\_path** _ key in adapter\_config json, once the model is saved with _ **save\_pretrained** _. I tried setting this same key in LoRA Config to whichever name I want but that’s not working correctly. This is an issue because when I try to load it again with _ **from\_pretrained** _, it sends out an error since it can’t find the correct base model, neither as a directory nor as a repo in Huggingface models.

For other info:  
Model: Custom Phi-3 implementation, but also causes issue with normal Phi-3  
OS: Linux(ubuntu)  
Huggingface version: 4.43.3  
PEFT version: 0.11.1

I think the following code should be able to reproduce the issue with a Phi-3 model:

```auto
from peft import LoraConfig, get_peft_model, prepare_model_for_kbit_training, AutoPeftModelForCausalLM, PeftModel, PeftConfig, PeftModelForCausalLM

from transformers import AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("/content/gdrive/My Drive/Colab Notebooks/DOE/src/models/weights/Phi-3-mini-128k-instruct")

peft_config = LoraConfig(**{
    "r": 16,
    "lora_alpha": 32,
    "lora_dropout": 0.05,
    "bias": "none",
    "task_type": "CAUSAL_LM",
    "target_modules": "all-linear",
    "modules_to_save": None,
    "base_model_name_or_path": "/content/gdrive/My Drive/Colab Notebooks/DOE/src/models/weights/Phi-3ex"
})

kbit_model = prepare_model_for_kbit_training(model)
peft_model = get_peft_model(kbit_model, peft_config)
peft_model.save_pretrained("/content/gdrive/MyDrive/Colab Notebooks/DOE/test_peft_model/phi-peft-v3")

```

The expected _ **base\_model\_name\_or\_path** _ key in adapter\_config should be _ **/content/gdrive/My Drive/Colab Notebooks/DOE/src/models/weights/Phi-3ex** _, but instead adapter\_config,json will contain following contents:

```auto
{
  "alpha_pattern": {},
  "auto_mapping": null,
  "base_model_name_or_path": "/content/gdrive/My Drive/Colab Notebooks/DOE/src/models/weights/Phi-3-mini-128k-instruct",
  "bias": "none",
  "fan_in_fan_out": false,
  "inference_mode": true,
  "init_lora_weights": true,
  "layer_replication": null,
  "layers_pattern": null,
  "layers_to_transform": null,
  "loftq_config": {},
  "lora_alpha": 32,
  "lora_dropout": 0.05,
  "megatron_config": null,
  "megatron_core": "megatron.core",
  "modules_to_save": null,
  "peft_type": "LORA",
  "r": 16,
  "rank_pattern": {},
  "revision": null,
  "target_modules": [
    "gate_up_proj",
    "o_proj",
    "qkv_proj",
    "down_proj"
  ],
  "task_type": "CAUSAL_LM",
  "use_dora": false,
  "use_rslora": false
}

```

I am not that well versed in this so I may have missed something, but currently its not working for me. I appreciate any help.