README.md

metadata

language:
  - ko
license: cc-by-nc-4.0
tags:
  - merge
  - mergekit
  - 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:

• LDCC/LDCC-SOLAR-10.7B
• upstage/SOLAR-10.7B-Instruct-v1.0

Github

https://github.com/sunjin7725/SOLAR-10.7b-slerp

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