File size: 5,936 Bytes
4b36abb |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 |
---
base_model:
- google/gemma-2-2b-it
tags:
- merge
- mergekit
- lazymergekit
- google/gemma-2-2b-it
---
# gemma-instruct-merge-test_
gemma-instruct-merge-test_ is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it)
## 🧩 Configuration
```yamlmodels:
- model: google/gemma-2-2b
- model: google/gemma-2-2b-it
parameters:
density:
- filter: model.layers.1.self_attn.q_proj
value: 0.00539
- filter: model.layers.2.self_attn.q_proj
value: 0.03843
- filter: model.layers.6.self_attn.q_proj
value: 0.03716
- filter: model.layers.24.self_attn.q_proj
value: 0.04552
- filter: model.layers.25.self_attn.q_proj
value: 0.03919
- filter: model.layers.0.self_attn.k_proj
value: 0.00592
- filter: model.layers.2.self_attn.k_proj
value: 0.02603
- filter: model.layers.3.self_attn.k_proj
value: 0.07283
- filter: model.layers.8.self_attn.k_proj
value: 0.08753
- filter: model.layers.10.self_attn.k_proj
value: 0.07783
- filter: model.layers.23.self_attn.k_proj
value: 0.05987
- filter: model.layers.24.self_attn.k_proj
value: 0.02903
- filter: model.layers.25.self_attn.k_proj
value: 0.08715
- filter: model.layers.0.self_attn.v_proj
value: 0.03025
- filter: model.layers.2.self_attn.v_proj
value: 0.00286
- filter: model.layers.3.self_attn.v_proj
value: 0.09155
- filter: model.layers.6.self_attn.v_proj
value: 0.06811
- filter: model.layers.7.self_attn.v_proj
value: 0.01334
- filter: model.layers.10.self_attn.v_proj
value: 0.04
- filter: model.layers.13.self_attn.v_proj
value: 0.09347
- filter: model.layers.24.self_attn.v_proj
value: 0.07956
- filter: model.layers.0.self_attn.o_proj
value: 0.03265
- filter: model.layers.2.self_attn.o_proj
value: 0.06134
- filter: model.layers.4.self_attn.o_proj
value: 0.07924
- filter: model.layers.6.self_attn.o_proj
value: 0.09982
- filter: model.layers.7.self_attn.o_proj
value: 0.02826
- filter: model.layers.8.self_attn.o_proj
value: 0.03906
- filter: model.layers.19.self_attn.o_proj
value: 0.09507
- filter: model.layers.23.self_attn.o_proj
value: 0.00282
- filter: model.layers.24.self_attn.o_proj
value: 0.09864
- filter: model.layers.25.self_attn.o_proj
value: 0.00961
- filter: model.layers.1.mlp.gate_proj
value: 0.08775
- filter: model.layers.2.mlp.gate_proj
value: 0.0001
- filter: model.layers.6.mlp.gate_proj
value: 0.06577
- filter: model.layers.12.mlp.gate_proj
value: 0.02651
- filter: model.layers.13.mlp.gate_proj
value: 0.04687
- filter: model.layers.15.mlp.gate_proj
value: 0.03147
- filter: model.layers.16.mlp.gate_proj
value: 0.05726
- filter: model.layers.17.mlp.gate_proj
value: 0.04511
- filter: model.layers.23.mlp.gate_proj
value: 0.08641
- filter: model.layers.1.mlp.up_proj
value: 0.06887
- filter: model.layers.6.mlp.up_proj
value: 0.07411
- filter: model.layers.7.mlp.up_proj
value: 0.05424
- filter: model.layers.12.mlp.up_proj
value: 0.08044
- filter: model.layers.13.mlp.up_proj
value: 0.0021
- filter: model.layers.14.mlp.up_proj
value: 0.26389
- filter: model.layers.15.mlp.up_proj
value: 0.06886
- filter: model.layers.23.mlp.up_proj
value: 0.02931
- filter: model.layers.0.mlp.down_proj
value: 0.06756
- filter: model.layers.1.mlp.down_proj
value: 0.03746
- filter: model.layers.2.mlp.down_proj
value: 0.09104
- filter: model.layers.3.mlp.down_proj
value: 0.06643
- filter: model.layers.4.mlp.down_proj
value: 0.05003
- filter: model.layers.5.mlp.down_proj
value: 0.0406
- filter: model.layers.6.mlp.down_proj
value: 0.01609
- filter: model.layers.7.mlp.down_proj
value: 0.09629
- filter: model.layers.8.mlp.down_proj
value: 0.08912
- filter: model.layers.10.mlp.down_proj
value: 0.04635
- filter: model.layers.11.mlp.down_proj
value: 0.0099
- filter: model.layers.12.mlp.down_proj
value: 0.03487
- filter: model.layers.13.mlp.down_proj
value: 0.04977
- filter: model.layers.14.mlp.down_proj
value: 0.00393
- filter: model.layers.15.mlp.down_proj
value: 0.00748
- filter: model.layers.16.mlp.down_proj
value: 0.06696
- filter: model.layers.17.mlp.down_proj
value: 0.02067
- filter: model.layers.19.mlp.down_proj
value: 0.009
- filter: model.layers.20.mlp.down_proj
value: 0.0215
- filter: model.layers.21.mlp.down_proj
value: 0.04196
- filter: model.layers.22.mlp.down_proj
value: 0.06326
- filter: model.layers.25.mlp.down_proj
value: 0.04905
weight:
- value: 1
merge_method: ties
base_model: google/gemma-2-2b
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
tokenizer_source: union
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "choprahetarth/gemma-instruct-merge-test_"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` |