# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("colable/llama2-ko-DPO")
model = AutoModelForMultimodalLM.from_pretrained("colable/llama2-ko-DPO")Quick Links
open-llama-2-ko based model with modified DPO dataset
This is an Korean Model based on
- [beomi/open-llama-2-ko-7b]
Dataset is modified from
- [SJ-Donald/orca-dpo-pairs-ko]
Parameters
learning_rate: float = 3e-4
lr_scheduler: str = "cosine"
warmup_ratio: float = 0.1
lora_r: int = 16
lora_alpha: int = 16
lora_dropout: float = 0.05
optim='paged_adamw_32bit'
bf16=True
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="colable/llama2-ko-DPO")