You_can_cry_Snowman-13B/README.md

language, library_name, pipeline_tag, license

language	library_name	pipeline_tag	license
ko	transformers	text-generation	cc-by-nc-sa-4.0

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.

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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.

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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)

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