Edit model card

Ko-PlatYi-6B-O

Model Details

Model Developers Kyujin Han (kyujinpy)

Input Models input text only.

Output Models generate text only.

Model Architecture
Ko-PlatYi-6B-O is an auto-regressive language model based on the Yi-34B transformer architecture.

Blog Link
Blog: [Coming soon...]
Github: [Coming soon...]

Base Model
beomi/Yi-Ko-6B

Training Dataset
kyujinpy/KOR-OpenOrca-Platypus-v3.

Model Benchmark

Open leaderboard

Follow up as link.

Model Average ARC HellaSwag MMLU TruthfulQA CommonGen-V2
Ko-PlatYi-6B-O 49.00 43.52 53.59 47.47 41.01 59.39
Ko-PlatYi-6B-kiwi 48.75 41.98 53.61 46.10 38.30 63.75
Ko-PlatYi-6B-gu 48.76 42.75 54.00 44.66 41.22 61.16
Ko-PlatYi-6B 49.97 43.00 53.55 46.50 40.31 66.47
Yi-Ko-6B 48.79 41.04 53.39 46.28 41.64 61.63

AI-Harness Evaluation

AI-Harness evaluation; link

Model BoolQ Copa HellaSwag Sentineg
Zero-shot
Ko-PlatYi-6B-O 0.3343 0.7687 0.4833 0.5794
Ko-PlatYi-6B-kiwi 0.3343 0.7665 0.4746 0.6248
Ko-PlatYi-6B-gu 0.7077 0.7696 0.4797 0.3979
Ko-PlatYi-6B 0.3343 0.7684 0.4917 0.5226
Yi-Ko-6B 0.7070 0.7696 0.5009 0.4044

Implementation Code

### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "kyujinpy/Ko-PlatYi-6B-O"
OpenOrca = AutoModelForCausalLM.from_pretrained(
        repo,
        return_dict=True,
        torch_dtype=torch.float16,
        device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
Downloads last month
1,251

Dataset used to train kyujinpy/Ko-PlatYi-6B-O