ashishpatel26 / llm-finetuning Goto Github PK

model = get_peft_model(model, peft_config)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-20-2327ea630778>](https://localhost:8080/#) in <cell line: 1>()
----> 1 model = get_peft_model(model, peft_config)
      2 model.print_trainable_parameters()

5 frames
[/usr/local/lib/python3.10/dist-packages/peft/tuners/tuners_utils.py](https://localhost:8080/#) in inject_adapter(self, model, adapter_name)
    303 
    304         if not is_target_modules_in_base_model:
--> 305             raise ValueError(
    306                 f"Target modules {peft_config.target_modules} not found in the base model. "
    307                 f"Please check the target modules and try again."

ValueError: Target modules {'Wqkv', 'out_proj'} not found in the base model. Please check the target modules and try again.

OSError: bn22/Mistral-7B-Instruct-v0.1-sharded is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>`

╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ in <cell line: 13>:13                                                                            │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/peft/utils/other.py:72 in                                │
│ prepare_model_for_int8_training                                                                  │
│                                                                                                  │
│    69 │                                                                                          │
│    70 │   if hasattr(model, output_embedding_layer_name):                                        │
│    71 │   │   output_embedding_layer = getattr(model, output_embedding_layer_name)               │
│ ❱  72 │   │   input_dtype = output_embedding_layer.weight.dtype                                  │
│    73 │   │                                                                                      │
│    74 │   │   class CastOutputToFloat(torch.nn.Sequential):                                      │
│    75 │   │   │   r"""                                                                           │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1614 in __getattr__           │
│                                                                                                  │
│   1611 │   │   │   modules = self.__dict__['_modules']                                           │
│   1612 │   │   │   if name in modules:                                                           │
│   1613 │   │   │   │   return modules[name]                                                      │
│ ❱ 1614 │   │   raise AttributeError("'{}' object has no attribute '{}'".format(                  │
│   1615 │   │   │   type(self).__name__, name))                                                   │
│   1616 │                                                                                         │
│   1617 │   def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:             │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
AttributeError: 'CastOutputToFloat' object has no attribute 'weight'