The license is cc-by-nc-sa-4.0.

🐻‍❄️You_can_cry_Snowman-13B🐻‍❄️

Model Details

Model Developers Seungyoo Lee(DopeorNope)

I am in charge of Large Language Models (LLMs) at Markr AI team in South Korea.

Input Models input text only.

Output Models generate text only.

Model Architecture
You_can_cry_Snowman-13B is an auto-regressive language model based on the SOLAR architecture.

Base Model

kyujinpy/Sakura-SOLAR-Instruct

Weyaxi/SauerkrautLM-UNA-SOLAR-Instruct

Implemented Method

I have merged two models by increasing the parameter size to create a larger model.

I wanted to check how much the performance of the SOLAR base model changes when the scale of the parameters is increased.

Implementation Code

Load model

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "DopeorNope/You_can_cry_Snowman-13B"
OpenOrca = AutoModelForCausalLM.from_pretrained(
        repo,
        return_dict=True,
        torch_dtype=torch.float16,
        device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)