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Ko-PlatYi-6B-gu
kyujinpy/Ko-PlatYi-6B-gu
Ko-PlatYi-6B-gu is a text generation model from kyujinpy. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as cc-by-nc-sa-4.0.
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46.1K
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Repo size
24.7 GB
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Repo makeup
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.bin12.4 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- llama
- Access
- Public
- Created
- Dec 2, 2023
- Updated
- Dec 9, 2023
- SHA
- b70b9d76
Datasets
Model card
From the Hugging Face model README
Ko-PlatYi-6B-gu
<img src='./Ko-PlatYi.png' width=256>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)
- Task
- Text Generation
- Library
- transformers
- Type
- llama
- License
- cc-by-nc-sa-4.0
- Languages
- ko
- Created
- Dec 2, 2023
- Updated
- Dec 9, 2023