metadata
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
SOLAR-10.7B-slerp
SOLAR-10.7B-slerp is a merge of the following models using mergekit:
Github
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
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
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