LED QA LoRA โ€” EXAONE-3.0-7.8B-Instruct

LoRA adapter fine-tuned on F1 technical regulations QA.

Base model

LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct

Training

  • Dataset: filtered/full Proposed QA SFT split
  • LoRA r=16, alpha=32, target=all linear projections
  • Epochs: 3
  • Max seq len: 2048

Load

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base = "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct"
adapter = "REPO_ID"

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