File size: 5,187 Bytes
4286500
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
---
base_model:
- bamec66557/VICIOUS_MESH-12B-BETA
- bamec66557/VICIOUS_MESH-12B-OMEGA
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 SLERP merge method.

### Models Merged

The following models were included in the merge:
* [bamec66557/VICIOUS_MESH-12B-BETA](https://huggingface.co/bamec66557/VICIOUS_MESH-12B-BETA)
* [bamec66557/VICIOUS_MESH-12B-OMEGA](https://huggingface.co/bamec66557/VICIOUS_MESH-12B-OMEGA)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: bamec66557/VICIOUS_MESH-12B-OMEGA
dtype: bfloat16
merge_method: slerp
tokenizer_source: base

# Slices Configuration (Layer-Specific Merging)
slices:
  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [0, 5]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [0, 5]
    parameters:
      t:
        - name: self_attn
          value: [0.85, 0.88, 0.91, 0.94, 0.97]
        - name: mlp
          value: [0.9, 0.92, 0.95, 0.98, 1.0]
        - name: layer_norm
          value: [0.75, 0.78, 0.81, 0.84, 0.87]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [5, 10]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [5, 10]
    parameters:
      t:
        - name: self_attn
          value: [0.8, 0.83, 0.86, 0.89, 0.92]
        - name: mlp
          value: [0.88, 0.91, 0.94, 0.97, 1.0]
        - name: layer_norm
          value: [0.7, 0.73, 0.76, 0.79, 0.82]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [10, 15]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [10, 15]
    parameters:
      t:
        - name: self_attn
          value: [0.75, 0.78, 0.81, 0.84, 0.87]
        - name: mlp
          value: [0.85, 0.88, 0.91, 0.94, 0.97]
        - name: layer_norm
          value: [0.65, 0.68, 0.71, 0.74, 0.77]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [15, 20]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [15, 20]
    parameters:
      t:
        - name: self_attn
          value: [0.72, 0.75, 0.78, 0.81, 0.84]
        - name: mlp
          value: [0.8, 0.83, 0.86, 0.89, 0.92]
        - name: layer_norm
          value: [0.6, 0.63, 0.66, 0.69, 0.72]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [20, 25]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [20, 25]
    parameters:
      t:
        - name: self_attn
          value: [0.7, 0.73, 0.76, 0.79, 0.82]
        - name: mlp
          value: [0.75, 0.78, 0.81, 0.84, 0.87]
        - name: layer_norm
          value: [0.55, 0.58, 0.61, 0.64, 0.67]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [25, 30]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [25, 30]
    parameters:
      t:
        - name: self_attn
          value: [0.68, 0.71, 0.74, 0.77, 0.8]
        - name: mlp
          value: [0.7, 0.73, 0.76, 0.79, 0.82]
        - name: layer_norm
          value: [0.5, 0.53, 0.56, 0.59, 0.62]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [30, 35]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [30, 35]
    parameters:
      t:
        - name: self_attn
          value: [0.65, 0.68, 0.71, 0.74, 0.77]
        - name: mlp
          value: [0.68, 0.71, 0.74, 0.77, 0.8]
        - name: layer_norm
          value: [0.45, 0.48, 0.51, 0.54, 0.57]
        - name: embed_tokens
          value: [1.0]

  - sources:
      - model: bamec66557/VICIOUS_MESH-12B-OMEGA
        layer_range: [35, 40]
      - model: bamec66557/VICIOUS_MESH-12B-BETA
        layer_range: [35, 40]
    parameters:
      t:
        - name: self_attn
          value: [0.6, 0.63, 0.66, 0.69, 0.72]
        - name: mlp
          value: [0.65, 0.68, 0.71, 0.74, 0.77]
        - name: layer_norm
          value: [0.4, 0.43, 0.46, 0.49, 0.52]
        - name: embed_tokens
          value: [1.0]

# Regularization
regularization:
  - method: weight_clipping
    clip_range: [-0.1, 0.1]
  - method: random_noise
    scale: 0.003
  - method: attention_dropout
    scale: 0.05
  - method: gradient_clipping
    clip_norm: 1.0

# Postprocessing
postprocessing:
  - operation: non_linear_scaling
    parameters:
      function: tanh
  - operation: sharpening
    intensity: 0.4
  - operation: gaussian_smoothing
    sigma: 1.0
  - operation: normalize
  - operation: dynamic_scaling
    scale_range: [0.85, 1.15]
  - operation: smoothing
    parameters:
      adaptive: true
      range: [0.9, 1.1]
      kernel_size: 3

```