from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base = "Qwen/Qwen2.5-VL-7B-Instruct"
adapter = "Ewengc21/qwen_qlora_dl_project"

tokenizer = AutoTokenizer.from_pretrained(base, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    base,
    device_map="auto",
    trust_remote_code=True
)
model = PeftModel.from_pretrained(model, adapter)

Training procedure

This model was trained with SFT.

Framework versions

PEFT 0.18.0
TRL: 0.26.1
Transformers: 4.57.3
Pytorch: 2.9.1+cu130
Datasets: 4.4.1
Tokenizers: 0.22.1

Citations

Cite TRL as:

bibtex

@misc{vonwerra2022trl,
	title        = {{TRL: Transformer Reinforcement Learning}},
	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}