Ko-PlatYi-6B-gu
Model Details
Model Developers Kyujin Han (kyujinpy)
Input Models input text only.
Output Models generate text only.
Model Architecture
Ko-PlatYi-6B-gu 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-gugugu-platypus-set.
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-gu"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)