File size: 2,829 Bytes
5a89e72
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
---
base_model:
- AlSamCur123/Mistral-Small3-24B-InstructContinuedFine
- trashpanda-org/MS-24B-Instruct-Mullein-v0
- huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated
library_name: transformers
tags:
- mergekit
- merge

---
# merge

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [DELLA](https://arxiv.org/abs/2406.11617) merge method using [huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated](https://huggingface.co/huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated) as a base.

### Models Merged

The following models were included in the merge:
* [AlSamCur123/Mistral-Small3-24B-InstructContinuedFine](https://huggingface.co/AlSamCur123/Mistral-Small3-24B-InstructContinuedFine)
* [trashpanda-org/MS-24B-Instruct-Mullein-v0](https://huggingface.co/trashpanda-org/MS-24B-Instruct-Mullein-v0)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
# 文件名: pcb_della_merge.yaml
merge_method: della  # 基于DELLA的自适应剪裁
base_model: huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated
models:
  - model: trashpanda-org/MS-24B-Instruct-Mullein-v0
    parameters:
      weight: 1.0  # 添加默认权重
      # PCB策略:限制层影响范围 + 动态竞争平衡
      layers:
        - layers: "8-16"
          parameter_name: density
          value: 0.4
        - layers: "8-16"
          parameter_name: epsilon
          value: 0.15
        - layers: "8-16"
          parameter_name: lambda
          value: 1.5
        - layers: "17-24"
          parameter_name: density
          value: 0.2
      variance_threshold: 0.3

  - model: AlSamCur123/Mistral-Small3-24B-InstructContinuedFine
    parameters:
      weight: 1.0  # 添加默认权重
      # 强化指令理解层
      layers:
        - layers: "0-12"
          parameter_name: density
          value: 0.7
        - layers: "0-12"
          parameter_name: epsilon
          value: 0.05
        - layers: "0-12"
          parameter_name: lambda
          value: 2.0
      variance_threshold: 0.25

  - model: huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated
    parameters:
      weight: 1.0  # 添加默认权重
      # 基模型参数保护策略
      density: 0.9          # 全局密度 (可能需要单独处理)
      layers:
        - layers: "12-24"
          parameter_name: density
          value: 1.0

parameters:
  global_density: 0.55      # 全局剪裁密度(PCB平衡点)
  intra_balance: true
  variance_threshold: 0.2
  epsilon_range: [0.1, 0.2]

tokenizer:
  source: base

# 参数压缩设置(实现12-13B目标)
architecture:
  hidden_size: 4096
  intermediate_size: 11008
  num_attention_heads: 32
  num_hidden_layers: 30
```