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---
language:
- ko
library_name: transformers
pipeline_tag: text-generation
license: cc-by-nc-sa-4.0
tags:
- merge
---
**The license is `cc-by-nc-sa-4.0`.**  
  
# **🐻‍❄️SOLARC-M-10.7B🐻‍❄️**  
![img](https://drive.google.com/uc?export=view&id=1_Qa2TfLMw3WeJ23dHkrP1Xln_RNt1jqG)  


## 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**  
SOLARC-M-10.7B is an auto-regressive language model based on the SOLAR architecture.

---

## **Base Model**  

[kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct)   
 

[jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1)


## **Implemented Method**

I have built a model using the merge method, utilizing each of these models as the base.


---
  
# Implementation Code


## Load model
```python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "DopeorNope/SOLARC-M-10.7B"
OpenOrca = AutoModelForCausalLM.from_pretrained(
        repo,
        return_dict=True,
        torch_dtype=torch.float16,
        device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
```


---