
# SOLAR-10.7B-slerp

SOLAR-10.7B-slerp is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [LDCC/LDCC-SOLAR-10.7B](https://huggingface.co/LDCC/LDCC-SOLAR-10.7B)
* [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)

## Github

[https://github.com/sunjin7725/SOLAR-10.7b-slerp](https://github.com/sunjin7725/SOLAR-10.7b-slerp)

## Benchmark

### Open-Ko-LLM-Leaderboard

| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
| ------: | -----: | -----------: | ------: | ------------: | --------------: |
|   56.93 |  53.58 |        62.03 |   53.31 |         57.16 |           58.56 |

## How to use

```Python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = 'SJ-Donald/SOLAR-10.7B-slerp'

tokenizer = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo,
    return_dict=True,
    torch_dtype=torch.float16,
    device_map='auto'
)
```


## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: LDCC/LDCC-SOLAR-10.7B
        layer_range: [0, 48]
      - model: upstage/SOLAR-10.7B-Instruct-v1.0
        layer_range: [0, 48]
merge_method: slerp
base_model: upstage/SOLAR-10.7B-Instruct-v1.0
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
tokenizer_source: union
dtype: float16

```
{"language": ["ko"], "license": "cc-by-nc-4.0", "tags": ["merge", "lazymergekit", "LDCC/LDCC-SOLAR-10.7B", "upstage/SOLAR-10.7B-Instruct-v1.0"], "base_model": ["LDCC/LDCC-SOLAR-10.7B", "upstage/SOLAR-10.7B-Instruct-v1.0"]}
transformers safetensors llama text-generation merge lazymergekit LDCC/LDCC-SOLAR-10.7B upstage/SOLAR-10.7B-Instruct-v1.0 conversational ko base_model:LDCC/LDCC-SOLAR-10.7B base_model:upstage/SOLAR-10.7B-Instruct-v1.0 license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us