Error when Using 8-bit Quantization

[JhonDan1999]

I am encountering a data type mismatch error when using 8-bit quantization with the PEFT library and SFTTrainer for fine-tuning a language model. The error occurs during the generation phase after loading the fine-tuned model.

Here's an overview of my workflow:

1. I fine-tuned a base model using the SFTTrainer from the TextRL library.
2. After fine-tuning, I saved the adapter using PEFT.
3. I loaded the fine-tuned model using PEFT and the BitsAndBytesConfig for 8-bit quantization.
4. I merged the adapter with the base model using merge_and_unload().
5. During the generation phase, I encountered a data type mismatch error.

Here's the code snippet for loading the fine-tuned model:

from peft import PeftConfig
config = PeftConfig.from_pretrained(peft_model_output_dir)

from transformers import AutoConfig, AutoModelForCausalLM

bnb_config = BitsAndBytesConfig(
    load_in_8bit=True,
    llm_int8_threshold=6.0,
    llm_int8_has_fp16_weight=True,
    bnb_4bit_compute_dtype=torch.float16,
    bnb_4bit_use_double_quant=False,
    bnb_4bit_quant_type="nf4"
)

base_model = AutoModelForCausalLM.from_pretrained(
    config.base_model_name_or_path,
    quantization_config=bnb_config,
    device_map='auto',
)

ft_model = PeftModel.from_pretrained(base_model, peft_model_output_dir)
ft_model = ft_model.merge_and_unload()

The error message I'm getting is:

RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != signed char

I have also printed the data types of the model parameters, and they appear to be a mix of torch.float16 and torch.int8, which is expected when using 8-bit quantization.

I would appreciate any guidance why am facing this issue

NOTE: this is you did not appear to me when I load the model in 4bits but after the fine-tuning I want to use the model in 8bits to get better accuracy (please correct me if my hypothesis is not correct)

[github-actions[bot]]

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

[JhonDan1999]

this still needs to be addressed

[younesbelkada]

Hi Thanks for the issue and apologies for the delay, what peft version are you using?

[JhonDan1999]

Hi @younesbelkada it is peft version: 0.11.1

[younesbelkada]

thanks! Can you print the model after merging it ? Alternatively can you share a model that we can look into on the Hub?

[github-actions[bot]]

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.