Upload folder using huggingface_hub
Browse files- README.md +358 -0
- chat_template.jinja +7 -0
- config.json +180 -0
- generation_config.json +7 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +0 -0
- recipe.yaml +834 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +4078 -0
README.md
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| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
license: other
|
| 4 |
+
license_name: lfm1.0
|
| 5 |
+
license_link: LICENSE
|
| 6 |
+
language:
|
| 7 |
+
- en
|
| 8 |
+
- ar
|
| 9 |
+
- zh
|
| 10 |
+
- fr
|
| 11 |
+
- de
|
| 12 |
+
- ja
|
| 13 |
+
- ko
|
| 14 |
+
- es
|
| 15 |
+
pipeline_tag: text-generation
|
| 16 |
+
tags:
|
| 17 |
+
- liquid
|
| 18 |
+
- lfm2
|
| 19 |
+
- edge
|
| 20 |
+
- moe
|
| 21 |
+
base_model: LiquidAI/LFM2-8B-A1B
|
| 22 |
+
---
|
| 23 |
+
|
| 24 |
+
<center>
|
| 25 |
+
<div style="text-align: center;">
|
| 26 |
+
<img
|
| 27 |
+
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/7_6D7rWrLxp2hb6OHSV1p.png"
|
| 28 |
+
alt="Liquid AI"
|
| 29 |
+
style="width: 100%; max-width: 66%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
|
| 30 |
+
/>
|
| 31 |
+
</div>
|
| 32 |
+
<div style="display: flex; justify-content: center;">
|
| 33 |
+
<a href="https://playground.liquid.ai/chat">
|
| 34 |
+
<svg width="114.8" height="20" viewBox="0 0 900 200" xmlns="http://www.w3.org/2000/svg" role="img" aria-label="Playground" style="margin-bottom: 1em;">
|
| 35 |
+
<title>Playground</title>
|
| 36 |
+
<g>
|
| 37 |
+
<rect fill="#fff" width="200" height="200"></rect>
|
| 38 |
+
<rect fill="url(#x)" x="200" width="800" height="200"></rect>
|
| 39 |
+
</g>
|
| 40 |
+
<g transform="translate(35, 30) scale(0.45, 0.45)">
|
| 41 |
+
<path d="M172.314 129.313L172.219 129.367L206.125 188.18C210.671 195.154 213.324 203.457 213.324 212.382C213.324 220.834 210.956 228.739 206.839 235.479L275.924 213.178L167.853 33.6L141.827 76.9614L172.314 129.313Z" fill="black"/>
|
| 42 |
+
<path d="M114.217 302.4L168.492 257.003C168.447 257.003 168.397 257.003 168.352 257.003C143.515 257.003 123.385 237.027 123.385 212.387C123.385 203.487 126.023 195.204 130.55 188.24L162.621 132.503L135.966 86.7327L60.0762 213.183L114.127 302.4H114.217Z" fill="black"/>
|
| 43 |
+
<path d="M191.435 250.681C191.435 250.681 191.43 250.681 191.425 250.686L129.71 302.4H221.294L267.71 226.593L191.435 250.686V250.681Z" fill="black"/>
|
| 44 |
+
</g>
|
| 45 |
+
<g transform="translate(50, 0)" aria-hidden="true" fill="#fff" text-anchor="start" font-family="Verdana,DejaVu Sans,sans-serif" font-size="110">
|
| 46 |
+
<text x="255" y="148" textLength="619" fill="#000" opacity="0.1">Playground</text>
|
| 47 |
+
<text x="245" y="138" textLength="619">Playground</text>
|
| 48 |
+
</g>
|
| 49 |
+
<linearGradient id="x" x1="0%" y1="0%" x2="100%" y2="0%">
|
| 50 |
+
<stop offset="0%" style="stop-color:#000000"></stop>
|
| 51 |
+
<stop offset="100%" style="stop-color:#000000"></stop>
|
| 52 |
+
</linearGradient>
|
| 53 |
+
</svg>
|
| 54 |
+
</a>
|
| 55 |
+
<a href="https://leap.liquid.ai/?utm_source=huggingface&utm_medium=modelcards">
|
| 56 |
+
<svg width="114.8" height="20" viewBox="0 0 900 200" xmlns="http://www.w3.org/2000/svg" role="img" aria-label="Leap" style="margin-bottom: 1em;">
|
| 57 |
+
<title>Leap</title>
|
| 58 |
+
<g>
|
| 59 |
+
<rect fill="#000" width="500" height="200"></rect>
|
| 60 |
+
</g>
|
| 61 |
+
<g transform="translate(100, 45) scale(3.5, 3.5)" fill="#fff">
|
| 62 |
+
<path d="M13.8512 28.0769C12.5435 28.0769 11.4025 27.8205 10.4281 27.3077C9.45375 26.7692 8.68452 26.0128 8.12042 25.0385C7.58196 24.0641 7.31273 22.9359 7.31273 21.6538V3.76923H0.389648V0H11.4666V21.6538C11.4666 22.4744 11.6973 23.1282 12.1589 23.6154C12.6204 24.0769 13.2486 24.3077 14.0435 24.3077H20.582V28.0769H13.8512Z"/>
|
| 63 |
+
<path d="M29.6439 28.4615C27.9259 28.4615 26.4131 28.1282 25.1054 27.4615C23.8233 26.7692 22.8362 25.8077 22.1439 24.5769C21.4516 23.3462 21.1054 21.9103 21.1054 20.2692V14.7308C21.1054 13.0641 21.4516 11.6282 22.1439 10.4231C22.8362 9.19231 23.8233 8.24359 25.1054 7.57692C26.4131 6.88462 27.9259 6.53846 29.6439 6.53846C31.3875 6.53846 32.9003 6.88462 34.1823 7.57692C35.4644 8.24359 36.4516 9.19231 37.1439 10.4231C37.8362 11.6282 38.1823 13.0641 38.1823 14.7308V18.5H25.1054V20.2692C25.1054 21.8333 25.49 23.0256 26.2592 23.8462C27.0541 24.6667 28.1951 25.0769 29.6823 25.0769C30.8875 25.0769 31.8618 24.8718 32.6054 24.4615C33.349 24.0256 33.8105 23.3974 33.99 22.5769H38.1054C37.7977 24.3718 36.8746 25.8077 35.3362 26.8846C33.7977 27.9359 31.9003 28.4615 29.6439 28.4615ZM34.1823 16V14.6923C34.1823 13.1538 33.7977 11.9615 33.0285 11.1154C32.2592 10.2692 31.131 9.84615 29.6439 9.84615C28.1823 9.84615 27.0541 10.2692 26.2592 11.1154C25.49 11.9615 25.1054 13.1667 25.1054 14.7308V15.6923L34.49 15.6538L34.1823 16Z"/>
|
| 64 |
+
<path d="M46.3596 28.4615C44.1545 28.4615 42.4109 27.8974 41.1288 26.7692C39.8724 25.6154 39.2442 24.0513 39.2442 22.0769C39.2442 20.0769 39.9109 18.5128 41.2442 17.3846C42.6032 16.2308 44.4622 15.6538 46.8211 15.6538H52.7058V13.6923C52.7058 12.5385 52.3468 11.641 51.6288 11C50.9109 10.359 49.8981 10.0385 48.5904 10.0385C47.4365 10.0385 46.475 10.2949 45.7058 10.8077C44.9365 11.2949 44.4878 11.9487 44.3596 12.7692H40.2827C40.5135 10.8718 41.3852 9.35897 42.8981 8.23077C44.4365 7.10256 46.3724 6.53846 48.7058 6.53846C51.2186 6.53846 53.2058 7.17949 54.6673 8.46154C56.1288 9.71795 56.8596 11.4359 56.8596 13.6154V28.0769H52.8211V24.1923H52.1288L52.8211 23.4231C52.8211 24.9615 52.2314 26.1923 51.0519 27.1154C49.8724 28.0128 48.3083 28.4615 46.3596 28.4615ZM47.5904 25.2692C49.0776 25.2692 50.2955 24.8974 51.2442 24.1538C52.2186 23.3846 52.7058 22.4103 52.7058 21.2308V18.4615H46.8981C45.8211 18.4615 44.9622 18.7564 44.3211 19.3462C43.7058 19.9359 43.3981 20.7436 43.3981 21.7692C43.3981 22.8462 43.7699 23.7051 44.5135 24.3462C45.257 24.9615 46.2827 25.2692 47.5904 25.2692Z"/>
|
| 65 |
+
<path d="M58.9984 35V6.92308H63.1138V10.9615H63.9984L63.1138 11.9231C63.1138 10.2564 63.6266 8.94872 64.6523 8C65.7036 7.02564 67.101 6.53846 68.8446 6.53846C70.9728 6.53846 72.6651 7.25641 73.9215 8.69231C75.2036 10.1026 75.8446 12.0385 75.8446 14.5V20.4615C75.8446 22.1026 75.5497 23.5256 74.96 24.7308C74.3959 25.9103 73.5882 26.8333 72.5369 27.5C71.5113 28.141 70.2805 28.4615 68.8446 28.4615C67.1266 28.4615 65.742 27.9872 64.6907 27.0385C63.6395 26.0641 63.1138 24.7436 63.1138 23.0769L63.9984 24.0385H63.0369L63.1523 28.9615V35H58.9984ZM67.4215 24.8462C68.7805 24.8462 69.8318 24.4615 70.5754 23.6923C71.3446 22.8974 71.7292 21.7564 71.7292 20.2692V14.7308C71.7292 13.2436 71.3446 12.1154 70.5754 11.3462C69.8318 10.5513 68.7805 10.1538 67.4215 10.1538C66.1138 10.1538 65.0754 10.5641 64.3061 11.3846C63.5369 12.1795 63.1523 13.2949 63.1523 14.7308V20.2692C63.1523 21.7051 63.5369 22.8333 64.3061 23.6538C65.0754 24.4487 66.1138 24.8462 67.4215 24.8462Z"/>
|
| 66 |
+
</g>
|
| 67 |
+
<linearGradient id="y" x1="0%" y1="0%" x2="100%" y2="0%">
|
| 68 |
+
<stop offset="0%" style="stop-color:#000000"></stop>
|
| 69 |
+
</linearGradient>
|
| 70 |
+
</svg>
|
| 71 |
+
</a>
|
| 72 |
+
</div>
|
| 73 |
+
</center>
|
| 74 |
+
|
| 75 |
+
# LFM2-8B-A1B
|
| 76 |
+
|
| 77 |
+
LFM2 is a new generation of hybrid models developed by [Liquid AI](https://www.liquid.ai/blog/lfm2-8b-a1b-an-efficient-on-device-mixture-of-experts), specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.
|
| 78 |
+
|
| 79 |
+
We're releasing the weights of our first MoE based on LFM2, with 8.3B total parameters and 1.5B active parameters.
|
| 80 |
+
|
| 81 |
+
- LFM2-8B-A1B is the best on-device MoE in terms of both **quality** (comparable to 3-4B dense models) and **speed** (faster than Qwen3-1.7B).
|
| 82 |
+
- **Code and knowledge** capabilities are significantly improved compared to LFM2-2.6B.
|
| 83 |
+
- Quantized variants fit comfortably on high-end **phones, tablets, and laptops**.
|
| 84 |
+
|
| 85 |
+
Find more information about LFM2-8B-A1B in our [blog post](https://www.liquid.ai/blog/).
|
| 86 |
+
|
| 87 |
+
## 📄 Model details
|
| 88 |
+
|
| 89 |
+
Due to their small size, **we recommend fine-tuning LFM2 models on narrow use cases** to maximize performance.
|
| 90 |
+
They are particularly suited for agentic tasks, data extraction, RAG, creative writing, and multi-turn conversations.
|
| 91 |
+
However, we do not recommend using them for tasks that are knowledge-intensive or require programming skills.
|
| 92 |
+
|
| 93 |
+
| Property | [**LFM2-8B-A1B**](https://huggingface.co/LiquidAI/LFM2-8B-A1B) |
|
| 94 |
+
| --------------------- | ----------------------------- |
|
| 95 |
+
| **Total parameters** | 8.3B |
|
| 96 |
+
| **Active parameters** | 1.5B |
|
| 97 |
+
| **Layers** | 24 (18 conv + 6 attn) |
|
| 98 |
+
| **Context length** | 32,768 tokens |
|
| 99 |
+
| **Vocabulary size** | 65,536 |
|
| 100 |
+
| **Training precision**| Mixed BF16/FP8 |
|
| 101 |
+
| **Training budget** | 12 trillion tokens |
|
| 102 |
+
| **License** | LFM Open License v1.0 |
|
| 103 |
+
|
| 104 |
+
**Supported languages**: English, Arabic, Chinese, French, German, Japanese, Korean, and Spanish.
|
| 105 |
+
|
| 106 |
+
**Generation parameters**: We recommend the following parameters:
|
| 107 |
+
* `temperature=0.3`
|
| 108 |
+
* `min_p=0.15`
|
| 109 |
+
* `repetition_penalty=1.05`
|
| 110 |
+
|
| 111 |
+
**Chat template**: LFM2 uses a ChatML-like chat template as follows:
|
| 112 |
+
|
| 113 |
+
```
|
| 114 |
+
<|startoftext|><|im_start|>system
|
| 115 |
+
You are a helpful assistant trained by Liquid AI.<|im_end|>
|
| 116 |
+
<|im_start|>user
|
| 117 |
+
What is C. elegans?<|im_end|>
|
| 118 |
+
<|im_start|>assistant
|
| 119 |
+
It's a tiny nematode that lives in temperate soil environments.<|im_end|>
|
| 120 |
+
```
|
| 121 |
+
|
| 122 |
+
You can automatically apply it using the dedicated [`.apply_chat_template()`](https://huggingface.co/docs/transformers/en/chat_templating#applychattemplate) function from Hugging Face transformers.
|
| 123 |
+
|
| 124 |
+
**Tool use**: It consists of four main steps:
|
| 125 |
+
1. **Function definition**: LFM2 takes JSON function definitions as input (JSON objects between `<|tool_list_start|>` and `<|tool_list_end|>` special tokens), usually in the system prompt
|
| 126 |
+
2. **Function call**: LFM2 writes Pythonic function calls (a Python list between `<|tool_call_start|>` and `<|tool_call_end|>` special tokens), as the assistant answer.
|
| 127 |
+
3. **Function execution**: The function call is executed and the result is returned (string between `<|tool_response_start|>` and `<|tool_response_end|>` special tokens), as a "tool" role.
|
| 128 |
+
4. **Final answer**: LFM2 interprets the outcome of the function call to address the original user prompt in plain text.
|
| 129 |
+
|
| 130 |
+
Here is a simple example of a conversation using tool use:
|
| 131 |
+
|
| 132 |
+
```
|
| 133 |
+
<|startoftext|><|im_start|>system
|
| 134 |
+
List of tools: <|tool_list_start|>[{"name": "get_candidate_status", "description": "Retrieves the current status of a candidate in the recruitment process", "parameters": {"type": "object", "properties": {"candidate_id": {"type": "string", "description": "Unique identifier for the candidate"}}, "required": ["candidate_id"]}}]<|tool_list_end|><|im_end|>
|
| 135 |
+
<|im_start|>user
|
| 136 |
+
What is the current status of candidate ID 12345?<|im_end|>
|
| 137 |
+
<|im_start|>assistant
|
| 138 |
+
<|tool_call_start|>[get_candidate_status(candidate_id="12345")]<|tool_call_end|>Checking the current status of candidate ID 12345.<|im_end|>
|
| 139 |
+
<|im_start|>tool
|
| 140 |
+
<|tool_response_start|>{"candidate_id": "12345", "status": "Interview Scheduled", "position": "Clinical Research Associate", "date": "2023-11-20"}<|tool_response_end|><|im_end|>
|
| 141 |
+
<|im_start|>assistant
|
| 142 |
+
The candidate with ID 12345 is currently in the "Interview Scheduled" stage for the position of Clinical Research Associate, with an interview date set for 2023-11-20.<|im_end|>
|
| 143 |
+
```
|
| 144 |
+
|
| 145 |
+
**Architecture**: Hybrid model with multiplicative gates and short convolutions: 18 double-gated short-range LIV convolution blocks and 6 grouped query attention (GQA) blocks.
|
| 146 |
+
|
| 147 |
+
**Pre-training mixture**: Approximately 75% English, 20% multilingual, and 5% code data sourced from the web and licensed materials.
|
| 148 |
+
|
| 149 |
+
**Training approach**:
|
| 150 |
+
* Very large-scale SFT on 50% downstream tasks, 50% general domains
|
| 151 |
+
* Custom DPO with length normalization and semi-online datasets
|
| 152 |
+
* Iterative model merging
|
| 153 |
+
|
| 154 |
+
## 🏃 How to run LFM2
|
| 155 |
+
|
| 156 |
+
### 1. Transformers
|
| 157 |
+
|
| 158 |
+
To run LFM2, you need to install Hugging Face [`transformers`](https://github.com/huggingface/transformers) from source as follows:
|
| 159 |
+
```bash
|
| 160 |
+
pip install git+https://github.com/huggingface/transformers.git@0c9a72e4576fe4c84077f066e585129c97bfd4e6
|
| 161 |
+
```
|
| 162 |
+
|
| 163 |
+
Here is an example of how to generate an answer with transformers in Python:
|
| 164 |
+
|
| 165 |
+
```python
|
| 166 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 167 |
+
|
| 168 |
+
# Load model and tokenizer
|
| 169 |
+
model_id = "LiquidAI/LFM2-8B-A1B"
|
| 170 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 171 |
+
model_id,
|
| 172 |
+
device_map="auto",
|
| 173 |
+
dtype="bfloat16",
|
| 174 |
+
# attn_implementation="flash_attention_2" <- uncomment on compatible GPU
|
| 175 |
+
)
|
| 176 |
+
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
| 177 |
+
|
| 178 |
+
# Generate answer
|
| 179 |
+
prompt = "What is C. elegans?"
|
| 180 |
+
input_ids = tokenizer.apply_chat_template(
|
| 181 |
+
[{"role": "user", "content": prompt}],
|
| 182 |
+
add_generation_prompt=True,
|
| 183 |
+
return_tensors="pt",
|
| 184 |
+
tokenize=True,
|
| 185 |
+
).to(model.device)
|
| 186 |
+
|
| 187 |
+
output = model.generate(
|
| 188 |
+
input_ids,
|
| 189 |
+
do_sample=True,
|
| 190 |
+
temperature=0.3,
|
| 191 |
+
min_p=0.15,
|
| 192 |
+
repetition_penalty=1.05,
|
| 193 |
+
max_new_tokens=512,
|
| 194 |
+
)
|
| 195 |
+
|
| 196 |
+
print(tokenizer.decode(output[0], skip_special_tokens=False))
|
| 197 |
+
|
| 198 |
+
# <|startoftext|><|im_start|>user
|
| 199 |
+
# What is C. elegans?<|im_end|>
|
| 200 |
+
# <|im_start|>assistant
|
| 201 |
+
# C. elegans, also known as Caenorhabditis elegans, is a small, free-living
|
| 202 |
+
# nematode worm (roundworm) that belongs to the phylum Nematoda.
|
| 203 |
+
```
|
| 204 |
+
|
| 205 |
+
You can directly run and test the model with this [Colab notebook](https://colab.research.google.com/drive/1i0u7X6qen9UJkV6xSCDZ0NmPUH50SOvO?usp=sharing).
|
| 206 |
+
|
| 207 |
+
### 2. vLLM
|
| 208 |
+
|
| 209 |
+
You can run the model in [`vLLM`](https://github.com/vllm-project/vllm) by building from source:
|
| 210 |
+
|
| 211 |
+
```bash
|
| 212 |
+
git clone https://github.com/vllm-project/vllm.git
|
| 213 |
+
cd vllm
|
| 214 |
+
pip install -e . -v
|
| 215 |
+
```
|
| 216 |
+
|
| 217 |
+
Here is an example of how to use it for inference:
|
| 218 |
+
|
| 219 |
+
```python
|
| 220 |
+
from vllm import LLM, SamplingParams
|
| 221 |
+
|
| 222 |
+
prompts = [
|
| 223 |
+
[
|
| 224 |
+
{
|
| 225 |
+
"content": "What is C. elegans?",
|
| 226 |
+
"role": "user",
|
| 227 |
+
},
|
| 228 |
+
],
|
| 229 |
+
[
|
| 230 |
+
{
|
| 231 |
+
"content": "Say hi in JSON format",
|
| 232 |
+
"role": "user",
|
| 233 |
+
},
|
| 234 |
+
],
|
| 235 |
+
[
|
| 236 |
+
{
|
| 237 |
+
"content": "Define AI in Spanish",
|
| 238 |
+
"role": "user",
|
| 239 |
+
},
|
| 240 |
+
],
|
| 241 |
+
]
|
| 242 |
+
|
| 243 |
+
sampling_params = SamplingParams(
|
| 244 |
+
temperature=0.3,
|
| 245 |
+
min_p=0.15,
|
| 246 |
+
repetition_penalty=1.05,
|
| 247 |
+
max_tokens=30
|
| 248 |
+
)
|
| 249 |
+
|
| 250 |
+
llm = LLM(model="LiquidAI/LFM2-8B-A1B", dtype="bfloat16")
|
| 251 |
+
|
| 252 |
+
outputs = llm.chat(prompts, sampling_params)
|
| 253 |
+
|
| 254 |
+
for i, output in enumerate(outputs):
|
| 255 |
+
prompt = prompts[i][0]["content"]
|
| 256 |
+
generated_text = output.outputs[0].text
|
| 257 |
+
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
|
| 258 |
+
```
|
| 259 |
+
|
| 260 |
+
|
| 261 |
+
### 3. llama.cpp
|
| 262 |
+
|
| 263 |
+
You can run LFM2 with llama.cpp using its [GGUF checkpoint](https://huggingface.co/LiquidAI/LFM2-8B-A1B-GGUF). Find more information in the model card.
|
| 264 |
+
|
| 265 |
+
## 🔧 How to fine-tune LFM2
|
| 266 |
+
|
| 267 |
+
We recommend fine-tuning LFM2 models on your use cases to maximize performance.
|
| 268 |
+
|
| 269 |
+
| Notebook | Description | Link |
|
| 270 |
+
|-------|------|------|
|
| 271 |
+
| SFT (TRL) | Supervised Fine-Tuning (SFT) notebook with a LoRA adapter using TRL. | <a href="https://colab.research.google.com/drive/1OXLEuSmzF4AjJ7yqRCDTn-ltvFjoGR9j?usp=sharing"><img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/vlOyMEjwHa_b_LXysEu2E.png" width="110" alt="Colab link"></a> |
|
| 272 |
+
| DPO (TRL) | Preference alignment with Direct Preference Optimization (DPO) using TRL. | <a href="https://colab.research.google.com/drive/1Q8hIHIQ8oofshcNYHUcYp1akUcZ-ufSn?usp=sharing"><img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/vlOyMEjwHa_b_LXysEu2E.png" width="110" alt="Colab link"></a> |
|
| 273 |
+
|
| 274 |
+
## 📈 Performance
|
| 275 |
+
|
| 276 |
+
### 1. Automated benchmarks
|
| 277 |
+
|
| 278 |
+
<div style="display: grid">
|
| 279 |
+
<div>
|
| 280 |
+
<a href="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/6xXgpyyK5htUZlHdpZab-.png" target="_blank">
|
| 281 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/6xXgpyyK5htUZlHdpZab-.png" alt="Benchmarks" style="width: 100%; height: auto; margin: 0; cursor: pointer;">
|
| 282 |
+
</a>
|
| 283 |
+
</div>
|
| 284 |
+
</div>
|
| 285 |
+
|
| 286 |
+
Compared to similar-sized models, LFM2-8B-A1B displays strong performance in instruction following and math while also running significantly faster.
|
| 287 |
+
|
| 288 |
+
| Model | MMLU | MMLU-Pro | GPQA | IFEval | IFBench | Multi-IF |
|
| 289 |
+
|---|---|---|---|---|---|---|
|
| 290 |
+
| **LFM2-8B-A1B** | 64.84 | 37.42 | 29.29 | 77.58 | 25.85 | 58.19 |
|
| 291 |
+
| LFM2-2.6B | 64.42 | 25.96 | 26.57 | 79.56 | 22.19 | 60.26 |
|
| 292 |
+
| Llama-3.2-3B-Instruct | 60.35 | 22.25 | 30.6 | 71.43 | 20.78 | 50.91 |
|
| 293 |
+
| SmolLM3-3B | 59.84 | 23.90 | 26.31 | 72.44 | 17.93 | 58.86 |
|
| 294 |
+
| gemma-3-4b-it | 58.35 | 34.76 | 29.51 | 76.85 | 23.53 | 66.61 |
|
| 295 |
+
| Qwen3-4B-Instruct-2507 | 72.25 | 52.31 | 34.85 | 85.62 | 30.28 | 75.54 |
|
| 296 |
+
| granite-4.0-h-tiny | 66.79 | 32.03 | 26.46 | 81.06 | 18.37 | 52.99 |
|
| 297 |
+
|
| 298 |
+
| Model | GSM8K | GSMPlus | MATH 500 | MATH Lvl 5 | MGSM | MMMLU |
|
| 299 |
+
|---|---|---|---|---|---|---|
|
| 300 |
+
| **LFM2-8B-A1B** | 84.38 | 64.76 | 74.2 | 62.38 | 72.4 | 55.26 |
|
| 301 |
+
| LFM2-2.6B | 82.41 | 60.75 | 63.6 | 54.38 | 74.32 | 55.39 |
|
| 302 |
+
| Llama-3.2-3B-Instruct | 75.21 | 38.68 | 41.2 | 24.06 | 61.68 | 47.92 |
|
| 303 |
+
| SmolLM3-3B | 81.12 | 58.91 | 73.6 | 51.93 | 68.72 | 50.02 |
|
| 304 |
+
| gemma-3-4b-it | 89.92 | 68.38 | 73.2 | 52.18 | 87.28 | 50.14 |
|
| 305 |
+
| Qwen3-4B-Instruct-2507 | 68.46 | 56.16 | 85.6 | 73.62 | 81.76 | 60.67 |
|
| 306 |
+
| granite-4.0-h-tiny | 82.64 | 59.14 | 58.2 | 36.11 | 73.68 | 56.13 |
|
| 307 |
+
|
| 308 |
+
| Model | Active params | LCB v6 | LCB v5 | HumanEval+ | Creative Writing v3 |
|
| 309 |
+
|----------------------------|---------------|---------------|---------------|--------------------|-----------------------------|
|
| 310 |
+
| **LFM2-8B-A1B** | 1.5B | 21.04% | 21.36% | 69.51% | 44.22% |
|
| 311 |
+
| Gemma-3-1b-it | 1B | 4.27% | 4.43% | 37.20% | 41.67% |
|
| 312 |
+
| Granite-4.0-h-tiny | 1B | 26.73% | 27.27% | 73.78% | 32.60% |
|
| 313 |
+
| Llama-3.2-1B-Instruct | 1.2B | 4.08% | 3.64% | 23.17% | 31.43% |
|
| 314 |
+
| Qwen2.5-1.5B-Instruct | 1.5B | 11.18% | 10.57% | 48.78% | 22.18% |
|
| 315 |
+
| Qwen3-1.7B (/no_think) | 1.7B | 24.07% | 26.48% | 60.98% | 31.56% |
|
| 316 |
+
| LFM2-2.6B | 2.6B | 14.41% | 14.43% | 57.93% | 38.79% |
|
| 317 |
+
| SmolLM3-3B | 3.1B | 19.05% | 19.20% | 60.37% | 36.44% |
|
| 318 |
+
| Llama-3.2-3B-Instruct | 3.2B | 11.47% | 11.48% | 24.06% | 38.84% |
|
| 319 |
+
| Qwen3-4B (/no_think) | 4B | 36.11% | 38.64% | 71.95% | 37.49% |
|
| 320 |
+
| Qwen3-4B-Instruct-2507 | 4B | 48.72% | 50.80% | 82.32% | 51.71% |
|
| 321 |
+
| Gemma-3-4b-it | 4.3B | 18.86% | 19.09% | 62.8% | 68.56% |
|
| 322 |
+
|
| 323 |
+
### 2. Inference
|
| 324 |
+
|
| 325 |
+
LFM2-8B-A1B is significantly faster than models with a similar number of active parameters, like Qwen3-1.7B.
|
| 326 |
+
|
| 327 |
+
<div style="display: grid; grid-template-columns: 1fr 1fr;">
|
| 328 |
+
<div>
|
| 329 |
+
<a href="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/AdR74EuIH_qJre89qaq62.png" target="_blank">
|
| 330 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/AdR74EuIH_qJre89qaq62.png" alt="Decode Throughput - S24 Ultra" style="width: 100%; height: auto; margin: 0; cursor: pointer;">
|
| 331 |
+
</a>
|
| 332 |
+
</div>
|
| 333 |
+
|
| 334 |
+
<div>
|
| 335 |
+
<a href="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/YzmQXbmcv5WuVJ1tI2Jbh.png" target="_blank">
|
| 336 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/YzmQXbmcv5WuVJ1tI2Jbh.png" alt="Decode Throughput - HX370" style="width: 100%; height: auto; margin: 0; cursor: pointer;">
|
| 337 |
+
</a>
|
| 338 |
+
</div>
|
| 339 |
+
</div>
|
| 340 |
+
|
| 341 |
+
The following plots showcase the performance of different models under int4 quantization with int8 dynamic activations on the AMD Ryzen AI 9 HX 370 CPU, using 16 threads. The results are obtained using our internal XNNPACK-based inference stack, and a custom CPU MoE kernel.
|
| 342 |
+
|
| 343 |
+
<div style="display: grid; grid-template-columns: 1fr 1fr;">
|
| 344 |
+
<div>
|
| 345 |
+
<a href="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/NC4XN11RJB-Ifh758os3e.png" target="_blank">
|
| 346 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/NC4XN11RJB-Ifh758os3e.png" alt="Prefill Throughput vs Sequence Length" style="width: 100%; height: auto; margin: 0; cursor: pointer;">
|
| 347 |
+
</a>
|
| 348 |
+
</div>
|
| 349 |
+
<div>
|
| 350 |
+
<a href="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/6oAenHRxKIyvJOgdCetlF.png" target="_blank">
|
| 351 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/6oAenHRxKIyvJOgdCetlF.png" alt="Decode Throughput vs Sequence Length" style="width: 100%; height: auto; margin: 0; cursor: pointer;">
|
| 352 |
+
</a>
|
| 353 |
+
</div>
|
| 354 |
+
</div>
|
| 355 |
+
|
| 356 |
+
## 📬 Contact
|
| 357 |
+
|
| 358 |
+
If you are interested in custom solutions with edge deployment, please contact [our sales team](https://www.liquid.ai/contact).
|
chat_template.jinja
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
| 1 |
+
{{- bos_token -}}{%- set system_prompt = "" -%}{%- set ns = namespace(system_prompt="") -%}{%- if messages[0]["role"] == "system" -%} {%- set ns.system_prompt = messages[0]["content"] -%} {%- set messages = messages[1:] -%}{%- endif -%}{%- if tools -%} {%- set ns.system_prompt = ns.system_prompt + ("
|
| 2 |
+
" if ns.system_prompt else "") + "List of tools: <|tool_list_start|>[" -%} {%- for tool in tools -%} {%- if tool is not string -%} {%- set tool = tool | tojson -%} {%- endif -%} {%- set ns.system_prompt = ns.system_prompt + tool -%} {%- if not loop.last -%} {%- set ns.system_prompt = ns.system_prompt + ", " -%} {%- endif -%} {%- endfor -%} {%- set ns.system_prompt = ns.system_prompt + "]<|tool_list_end|>" -%}{%- endif -%}{%- if ns.system_prompt -%} {{- "<|im_start|>system
|
| 3 |
+
" + ns.system_prompt + "<|im_end|>
|
| 4 |
+
" -}}{%- endif -%}{%- for message in messages -%} {{- "<|im_start|>" + message["role"] + "
|
| 5 |
+
" -}} {%- set content = message["content"] -%} {%- if content is not string -%} {%- set content = content | tojson -%} {%- endif -%} {%- if message["role"] == "tool" -%} {%- set content = "<|tool_response_start|>" + content + "<|tool_response_end|>" -%} {%- endif -%} {{- content + "<|im_end|>
|
| 6 |
+
" -}}{%- endfor -%}{%- if add_generation_prompt -%} {{- "<|im_start|>assistant
|
| 7 |
+
" -}}{%- endif -%}
|
config.json
ADDED
|
@@ -0,0 +1,180 @@
|
|
|
|
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|
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| 1 |
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| 30 |
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| 31 |
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|
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|
| 179 |
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|
| 180 |
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generation_config.json
ADDED
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| 7 |
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ADDED
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ADDED
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ADDED
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recipe.yaml
ADDED
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|
|
| 1 |
+
default_stage:
|
| 2 |
+
default_modifiers:
|
| 3 |
+
AWQModifier:
|
| 4 |
+
config_groups:
|
| 5 |
+
group_0:
|
| 6 |
+
targets: [Linear]
|
| 7 |
+
weights:
|
| 8 |
+
num_bits: 4
|
| 9 |
+
type: int
|
| 10 |
+
symmetric: true
|
| 11 |
+
group_size: 32
|
| 12 |
+
strategy: group
|
| 13 |
+
block_structure: null
|
| 14 |
+
dynamic: false
|
| 15 |
+
actorder: null
|
| 16 |
+
observer: mse
|
| 17 |
+
observer_kwargs: {}
|
| 18 |
+
input_activations: null
|
| 19 |
+
output_activations: null
|
| 20 |
+
format: null
|
| 21 |
+
targets: [Linear]
|
| 22 |
+
ignore: [model.embed_tokens, model.embedding_norm, 're:model[.]layers[.]0[.].*', 're:model[.]layers[.]1[.].*',
|
| 23 |
+
're:.*feed_forward[.]gate$', 're:.*ffn_norm$', 're:.*operator_norm$', 're:.*self_attn.*',
|
| 24 |
+
're:.*conv.*', lm_head]
|
| 25 |
+
mappings:
|
| 26 |
+
- smooth_layer: model.layers.0.operator_norm
|
| 27 |
+
balance_layers: [model.layers.0.conv.in_proj]
|
| 28 |
+
- smooth_layer: model.layers.0.ffn_norm
|
| 29 |
+
balance_layers: [model.layers.0.feed_forward.w1, model.layers.0.feed_forward.w3]
|
| 30 |
+
- smooth_layer: model.layers.1.operator_norm
|
| 31 |
+
balance_layers: [model.layers.1.conv.in_proj]
|
| 32 |
+
- smooth_layer: model.layers.1.ffn_norm
|
| 33 |
+
balance_layers: [model.layers.1.feed_forward.w1, model.layers.1.feed_forward.w3]
|
| 34 |
+
- smooth_layer: model.layers.2.operator_norm
|
| 35 |
+
balance_layers: [model.layers.2.self_attn.q_proj, model.layers.2.self_attn.k_proj,
|
| 36 |
+
model.layers.2.self_attn.v_proj]
|
| 37 |
+
- smooth_layer: model.layers.2.ffn_norm
|
| 38 |
+
balance_layers: [model.layers.2.feed_forward.gate, model.layers.2.feed_forward.experts.0.w1,
|
| 39 |
+
model.layers.2.feed_forward.experts.0.w3, model.layers.2.feed_forward.experts.1.w1,
|
| 40 |
+
model.layers.2.feed_forward.experts.1.w3, model.layers.2.feed_forward.experts.2.w1,
|
| 41 |
+
model.layers.2.feed_forward.experts.2.w3, model.layers.2.feed_forward.experts.3.w1,
|
| 42 |
+
model.layers.2.feed_forward.experts.3.w3, model.layers.2.feed_forward.experts.4.w1,
|
| 43 |
+
model.layers.2.feed_forward.experts.4.w3, model.layers.2.feed_forward.experts.5.w1,
|
| 44 |
+
model.layers.2.feed_forward.experts.5.w3, model.layers.2.feed_forward.experts.6.w1,
|
| 45 |
+
model.layers.2.feed_forward.experts.6.w3, model.layers.2.feed_forward.experts.7.w1,
|
| 46 |
+
model.layers.2.feed_forward.experts.7.w3, model.layers.2.feed_forward.experts.8.w1,
|
| 47 |
+
model.layers.2.feed_forward.experts.8.w3, model.layers.2.feed_forward.experts.9.w1,
|
| 48 |
+
model.layers.2.feed_forward.experts.9.w3, model.layers.2.feed_forward.experts.10.w1,
|
| 49 |
+
model.layers.2.feed_forward.experts.10.w3, model.layers.2.feed_forward.experts.11.w1,
|
| 50 |
+
model.layers.2.feed_forward.experts.11.w3, model.layers.2.feed_forward.experts.12.w1,
|
| 51 |
+
model.layers.2.feed_forward.experts.12.w3, model.layers.2.feed_forward.experts.13.w1,
|
| 52 |
+
model.layers.2.feed_forward.experts.13.w3, model.layers.2.feed_forward.experts.14.w1,
|
| 53 |
+
model.layers.2.feed_forward.experts.14.w3, model.layers.2.feed_forward.experts.15.w1,
|
| 54 |
+
model.layers.2.feed_forward.experts.15.w3, model.layers.2.feed_forward.experts.16.w1,
|
| 55 |
+
model.layers.2.feed_forward.experts.16.w3, model.layers.2.feed_forward.experts.17.w1,
|
| 56 |
+
model.layers.2.feed_forward.experts.17.w3, model.layers.2.feed_forward.experts.18.w1,
|
| 57 |
+
model.layers.2.feed_forward.experts.18.w3, model.layers.2.feed_forward.experts.19.w1,
|
| 58 |
+
model.layers.2.feed_forward.experts.19.w3, model.layers.2.feed_forward.experts.20.w1,
|
| 59 |
+
model.layers.2.feed_forward.experts.20.w3, model.layers.2.feed_forward.experts.21.w1,
|
| 60 |
+
model.layers.2.feed_forward.experts.21.w3, model.layers.2.feed_forward.experts.22.w1,
|
| 61 |
+
model.layers.2.feed_forward.experts.22.w3, model.layers.2.feed_forward.experts.23.w1,
|
| 62 |
+
model.layers.2.feed_forward.experts.23.w3, model.layers.2.feed_forward.experts.24.w1,
|
| 63 |
+
model.layers.2.feed_forward.experts.24.w3, model.layers.2.feed_forward.experts.25.w1,
|
| 64 |
+
model.layers.2.feed_forward.experts.25.w3, model.layers.2.feed_forward.experts.26.w1,
|
| 65 |
+
model.layers.2.feed_forward.experts.26.w3, model.layers.2.feed_forward.experts.27.w1,
|
| 66 |
+
model.layers.2.feed_forward.experts.27.w3, model.layers.2.feed_forward.experts.28.w1,
|
| 67 |
+
model.layers.2.feed_forward.experts.28.w3, model.layers.2.feed_forward.experts.29.w1,
|
| 68 |
+
model.layers.2.feed_forward.experts.29.w3, model.layers.2.feed_forward.experts.30.w1,
|
| 69 |
+
model.layers.2.feed_forward.experts.30.w3, model.layers.2.feed_forward.experts.31.w1,
|
| 70 |
+
model.layers.2.feed_forward.experts.31.w3]
|
| 71 |
+
- smooth_layer: model.layers.3.operator_norm
|
| 72 |
+
balance_layers: [model.layers.3.conv.in_proj]
|
| 73 |
+
- smooth_layer: model.layers.3.ffn_norm
|
| 74 |
+
balance_layers: [model.layers.3.feed_forward.gate, model.layers.3.feed_forward.experts.0.w1,
|
| 75 |
+
model.layers.3.feed_forward.experts.0.w3, model.layers.3.feed_forward.experts.1.w1,
|
| 76 |
+
model.layers.3.feed_forward.experts.1.w3, model.layers.3.feed_forward.experts.2.w1,
|
| 77 |
+
model.layers.3.feed_forward.experts.2.w3, model.layers.3.feed_forward.experts.3.w1,
|
| 78 |
+
model.layers.3.feed_forward.experts.3.w3, model.layers.3.feed_forward.experts.4.w1,
|
| 79 |
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model.layers.3.feed_forward.experts.4.w3, model.layers.3.feed_forward.experts.5.w1,
|
| 80 |
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model.layers.3.feed_forward.experts.5.w3, model.layers.3.feed_forward.experts.6.w1,
|
| 81 |
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model.layers.3.feed_forward.experts.6.w3, model.layers.3.feed_forward.experts.7.w1,
|
| 82 |
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model.layers.3.feed_forward.experts.7.w3, model.layers.3.feed_forward.experts.8.w1,
|
| 83 |
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model.layers.3.feed_forward.experts.8.w3, model.layers.3.feed_forward.experts.9.w1,
|
| 84 |
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model.layers.3.feed_forward.experts.9.w3, model.layers.3.feed_forward.experts.10.w1,
|
| 85 |
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model.layers.3.feed_forward.experts.10.w3, model.layers.3.feed_forward.experts.11.w1,
|
| 86 |
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model.layers.3.feed_forward.experts.11.w3, model.layers.3.feed_forward.experts.12.w1,
|
| 87 |
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model.layers.3.feed_forward.experts.12.w3, model.layers.3.feed_forward.experts.13.w1,
|
| 88 |
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model.layers.3.feed_forward.experts.13.w3, model.layers.3.feed_forward.experts.14.w1,
|
| 89 |
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model.layers.3.feed_forward.experts.14.w3, model.layers.3.feed_forward.experts.15.w1,
|
| 90 |
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model.layers.3.feed_forward.experts.15.w3, model.layers.3.feed_forward.experts.16.w1,
|
| 91 |
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model.layers.3.feed_forward.experts.16.w3, model.layers.3.feed_forward.experts.17.w1,
|
| 92 |
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model.layers.3.feed_forward.experts.17.w3, model.layers.3.feed_forward.experts.18.w1,
|
| 93 |
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model.layers.3.feed_forward.experts.18.w3, model.layers.3.feed_forward.experts.19.w1,
|
| 94 |
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model.layers.3.feed_forward.experts.19.w3, model.layers.3.feed_forward.experts.20.w1,
|
| 95 |
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model.layers.3.feed_forward.experts.20.w3, model.layers.3.feed_forward.experts.21.w1,
|
| 96 |
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model.layers.3.feed_forward.experts.21.w3, model.layers.3.feed_forward.experts.22.w1,
|
| 97 |
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model.layers.3.feed_forward.experts.22.w3, model.layers.3.feed_forward.experts.23.w1,
|
| 98 |
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model.layers.3.feed_forward.experts.23.w3, model.layers.3.feed_forward.experts.24.w1,
|
| 99 |
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model.layers.3.feed_forward.experts.24.w3, model.layers.3.feed_forward.experts.25.w1,
|
| 100 |
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model.layers.3.feed_forward.experts.25.w3, model.layers.3.feed_forward.experts.26.w1,
|
| 101 |
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model.layers.3.feed_forward.experts.26.w3, model.layers.3.feed_forward.experts.27.w1,
|
| 102 |
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model.layers.3.feed_forward.experts.27.w3, model.layers.3.feed_forward.experts.28.w1,
|
| 103 |
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model.layers.3.feed_forward.experts.28.w3, model.layers.3.feed_forward.experts.29.w1,
|
| 104 |
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model.layers.3.feed_forward.experts.29.w3, model.layers.3.feed_forward.experts.30.w1,
|
| 105 |
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model.layers.3.feed_forward.experts.30.w3, model.layers.3.feed_forward.experts.31.w1,
|
| 106 |
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model.layers.3.feed_forward.experts.31.w3]
|
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|
| 108 |
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balance_layers: [model.layers.4.conv.in_proj]
|
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|
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|
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model.layers.4.feed_forward.experts.0.w3, model.layers.4.feed_forward.experts.1.w1,
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model.layers.4.feed_forward.experts.1.w3, model.layers.4.feed_forward.experts.2.w1,
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model.layers.4.feed_forward.experts.2.w3, model.layers.4.feed_forward.experts.3.w1,
|
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model.layers.4.feed_forward.experts.3.w3, model.layers.4.feed_forward.experts.4.w1,
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model.layers.4.feed_forward.experts.4.w3, model.layers.4.feed_forward.experts.5.w1,
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model.layers.4.feed_forward.experts.5.w3, model.layers.4.feed_forward.experts.6.w1,
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model.layers.4.feed_forward.experts.6.w3, model.layers.4.feed_forward.experts.7.w1,
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model.layers.4.feed_forward.experts.7.w3, model.layers.4.feed_forward.experts.8.w1,
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model.layers.4.feed_forward.experts.8.w3, model.layers.4.feed_forward.experts.9.w1,
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model.layers.4.feed_forward.experts.9.w3, model.layers.4.feed_forward.experts.10.w1,
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model.layers.4.feed_forward.experts.10.w3, model.layers.4.feed_forward.experts.11.w1,
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model.layers.4.feed_forward.experts.11.w3, model.layers.4.feed_forward.experts.12.w1,
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| 123 |
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model.layers.4.feed_forward.experts.12.w3, model.layers.4.feed_forward.experts.13.w1,
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| 124 |
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model.layers.4.feed_forward.experts.13.w3, model.layers.4.feed_forward.experts.14.w1,
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model.layers.4.feed_forward.experts.14.w3, model.layers.4.feed_forward.experts.15.w1,
|
| 126 |
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model.layers.4.feed_forward.experts.15.w3, model.layers.4.feed_forward.experts.16.w1,
|
| 127 |
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model.layers.4.feed_forward.experts.16.w3, model.layers.4.feed_forward.experts.17.w1,
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| 128 |
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model.layers.4.feed_forward.experts.17.w3, model.layers.4.feed_forward.experts.18.w1,
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| 129 |
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model.layers.4.feed_forward.experts.18.w3, model.layers.4.feed_forward.experts.19.w1,
|
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model.layers.4.feed_forward.experts.19.w3, model.layers.4.feed_forward.experts.20.w1,
|
| 131 |
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model.layers.4.feed_forward.experts.20.w3, model.layers.4.feed_forward.experts.21.w1,
|
| 132 |
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model.layers.4.feed_forward.experts.21.w3, model.layers.4.feed_forward.experts.22.w1,
|
| 133 |
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model.layers.4.feed_forward.experts.22.w3, model.layers.4.feed_forward.experts.23.w1,
|
| 134 |
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model.layers.4.feed_forward.experts.23.w3, model.layers.4.feed_forward.experts.24.w1,
|
| 135 |
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model.layers.4.feed_forward.experts.24.w3, model.layers.4.feed_forward.experts.25.w1,
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model.layers.4.feed_forward.experts.25.w3, model.layers.4.feed_forward.experts.26.w1,
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| 137 |
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model.layers.4.feed_forward.experts.26.w3, model.layers.4.feed_forward.experts.27.w1,
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| 138 |
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model.layers.4.feed_forward.experts.27.w3, model.layers.4.feed_forward.experts.28.w1,
|
| 139 |
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model.layers.4.feed_forward.experts.28.w3, model.layers.4.feed_forward.experts.29.w1,
|
| 140 |
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model.layers.4.feed_forward.experts.29.w3, model.layers.4.feed_forward.experts.30.w1,
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| 141 |
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model.layers.4.feed_forward.experts.30.w3, model.layers.4.feed_forward.experts.31.w1,
|
| 142 |
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model.layers.4.feed_forward.experts.31.w3]
|
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|
| 144 |
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|
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|
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|
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model.layers.5.feed_forward.experts.0.w3, model.layers.5.feed_forward.experts.1.w1,
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model.layers.5.feed_forward.experts.1.w3, model.layers.5.feed_forward.experts.2.w1,
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model.layers.5.feed_forward.experts.2.w3, model.layers.5.feed_forward.experts.3.w1,
|
| 150 |
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model.layers.5.feed_forward.experts.3.w3, model.layers.5.feed_forward.experts.4.w1,
|
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model.layers.5.feed_forward.experts.4.w3, model.layers.5.feed_forward.experts.5.w1,
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model.layers.5.feed_forward.experts.5.w3, model.layers.5.feed_forward.experts.6.w1,
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model.layers.5.feed_forward.experts.6.w3, model.layers.5.feed_forward.experts.7.w1,
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model.layers.5.feed_forward.experts.7.w3, model.layers.5.feed_forward.experts.8.w1,
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model.layers.5.feed_forward.experts.8.w3, model.layers.5.feed_forward.experts.9.w1,
|
| 156 |
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model.layers.5.feed_forward.experts.9.w3, model.layers.5.feed_forward.experts.10.w1,
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| 157 |
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model.layers.5.feed_forward.experts.10.w3, model.layers.5.feed_forward.experts.11.w1,
|
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model.layers.5.feed_forward.experts.11.w3, model.layers.5.feed_forward.experts.12.w1,
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| 159 |
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model.layers.5.feed_forward.experts.12.w3, model.layers.5.feed_forward.experts.13.w1,
|
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model.layers.5.feed_forward.experts.13.w3, model.layers.5.feed_forward.experts.14.w1,
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| 161 |
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model.layers.5.feed_forward.experts.14.w3, model.layers.5.feed_forward.experts.15.w1,
|
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model.layers.5.feed_forward.experts.15.w3, model.layers.5.feed_forward.experts.16.w1,
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| 163 |
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model.layers.5.feed_forward.experts.16.w3, model.layers.5.feed_forward.experts.17.w1,
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| 164 |
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model.layers.5.feed_forward.experts.17.w3, model.layers.5.feed_forward.experts.18.w1,
|
| 165 |
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model.layers.5.feed_forward.experts.18.w3, model.layers.5.feed_forward.experts.19.w1,
|
| 166 |
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model.layers.5.feed_forward.experts.19.w3, model.layers.5.feed_forward.experts.20.w1,
|
| 167 |
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model.layers.5.feed_forward.experts.20.w3, model.layers.5.feed_forward.experts.21.w1,
|
| 168 |
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model.layers.5.feed_forward.experts.21.w3, model.layers.5.feed_forward.experts.22.w1,
|
| 169 |
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model.layers.5.feed_forward.experts.22.w3, model.layers.5.feed_forward.experts.23.w1,
|
| 170 |
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model.layers.5.feed_forward.experts.23.w3, model.layers.5.feed_forward.experts.24.w1,
|
| 171 |
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model.layers.5.feed_forward.experts.24.w3, model.layers.5.feed_forward.experts.25.w1,
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| 172 |
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model.layers.5.feed_forward.experts.25.w3, model.layers.5.feed_forward.experts.26.w1,
|
| 173 |
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model.layers.5.feed_forward.experts.26.w3, model.layers.5.feed_forward.experts.27.w1,
|
| 174 |
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model.layers.5.feed_forward.experts.27.w3, model.layers.5.feed_forward.experts.28.w1,
|
| 175 |
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model.layers.5.feed_forward.experts.28.w3, model.layers.5.feed_forward.experts.29.w1,
|
| 176 |
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model.layers.5.feed_forward.experts.29.w3, model.layers.5.feed_forward.experts.30.w1,
|
| 177 |
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model.layers.5.feed_forward.experts.30.w3, model.layers.5.feed_forward.experts.31.w1,
|
| 178 |
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model.layers.5.feed_forward.experts.31.w3]
|
| 179 |
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|
| 180 |
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balance_layers: [model.layers.6.self_attn.q_proj, model.layers.6.self_attn.k_proj,
|
| 181 |
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model.layers.6.self_attn.v_proj]
|
| 182 |
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|
| 183 |
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balance_layers: [model.layers.6.feed_forward.gate, model.layers.6.feed_forward.experts.0.w1,
|
| 184 |
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model.layers.6.feed_forward.experts.0.w3, model.layers.6.feed_forward.experts.1.w1,
|
| 185 |
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model.layers.6.feed_forward.experts.1.w3, model.layers.6.feed_forward.experts.2.w1,
|
| 186 |
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model.layers.6.feed_forward.experts.2.w3, model.layers.6.feed_forward.experts.3.w1,
|
| 187 |
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model.layers.6.feed_forward.experts.3.w3, model.layers.6.feed_forward.experts.4.w1,
|
| 188 |
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model.layers.6.feed_forward.experts.4.w3, model.layers.6.feed_forward.experts.5.w1,
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model.layers.6.feed_forward.experts.5.w3, model.layers.6.feed_forward.experts.6.w1,
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model.layers.6.feed_forward.experts.6.w3, model.layers.6.feed_forward.experts.7.w1,
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model.layers.6.feed_forward.experts.7.w3, model.layers.6.feed_forward.experts.8.w1,
|
| 192 |
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model.layers.6.feed_forward.experts.8.w3, model.layers.6.feed_forward.experts.9.w1,
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| 193 |
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model.layers.6.feed_forward.experts.9.w3, model.layers.6.feed_forward.experts.10.w1,
|
| 194 |
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model.layers.6.feed_forward.experts.10.w3, model.layers.6.feed_forward.experts.11.w1,
|
| 195 |
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model.layers.6.feed_forward.experts.11.w3, model.layers.6.feed_forward.experts.12.w1,
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model.layers.6.feed_forward.experts.12.w3, model.layers.6.feed_forward.experts.13.w1,
|
| 197 |
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model.layers.6.feed_forward.experts.13.w3, model.layers.6.feed_forward.experts.14.w1,
|
| 198 |
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model.layers.6.feed_forward.experts.14.w3, model.layers.6.feed_forward.experts.15.w1,
|
| 199 |
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model.layers.6.feed_forward.experts.15.w3, model.layers.6.feed_forward.experts.16.w1,
|
| 200 |
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model.layers.6.feed_forward.experts.16.w3, model.layers.6.feed_forward.experts.17.w1,
|
| 201 |
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model.layers.6.feed_forward.experts.17.w3, model.layers.6.feed_forward.experts.18.w1,
|
| 202 |
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model.layers.6.feed_forward.experts.18.w3, model.layers.6.feed_forward.experts.19.w1,
|
| 203 |
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model.layers.6.feed_forward.experts.19.w3, model.layers.6.feed_forward.experts.20.w1,
|
| 204 |
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model.layers.6.feed_forward.experts.20.w3, model.layers.6.feed_forward.experts.21.w1,
|
| 205 |
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model.layers.6.feed_forward.experts.21.w3, model.layers.6.feed_forward.experts.22.w1,
|
| 206 |
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model.layers.6.feed_forward.experts.22.w3, model.layers.6.feed_forward.experts.23.w1,
|
| 207 |
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model.layers.6.feed_forward.experts.23.w3, model.layers.6.feed_forward.experts.24.w1,
|
| 208 |
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model.layers.6.feed_forward.experts.24.w3, model.layers.6.feed_forward.experts.25.w1,
|
| 209 |
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model.layers.6.feed_forward.experts.25.w3, model.layers.6.feed_forward.experts.26.w1,
|
| 210 |
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model.layers.6.feed_forward.experts.26.w3, model.layers.6.feed_forward.experts.27.w1,
|
| 211 |
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model.layers.6.feed_forward.experts.27.w3, model.layers.6.feed_forward.experts.28.w1,
|
| 212 |
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model.layers.6.feed_forward.experts.28.w3, model.layers.6.feed_forward.experts.29.w1,
|
| 213 |
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model.layers.6.feed_forward.experts.29.w3, model.layers.6.feed_forward.experts.30.w1,
|
| 214 |
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model.layers.6.feed_forward.experts.30.w3, model.layers.6.feed_forward.experts.31.w1,
|
| 215 |
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model.layers.6.feed_forward.experts.31.w3]
|
| 216 |
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|
| 217 |
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balance_layers: [model.layers.7.conv.in_proj]
|
| 218 |
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|
| 219 |
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balance_layers: [model.layers.7.feed_forward.gate, model.layers.7.feed_forward.experts.0.w1,
|
| 220 |
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model.layers.7.feed_forward.experts.0.w3, model.layers.7.feed_forward.experts.1.w1,
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model.layers.7.feed_forward.experts.1.w3, model.layers.7.feed_forward.experts.2.w1,
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model.layers.7.feed_forward.experts.2.w3, model.layers.7.feed_forward.experts.3.w1,
|
| 223 |
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model.layers.7.feed_forward.experts.3.w3, model.layers.7.feed_forward.experts.4.w1,
|
| 224 |
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model.layers.7.feed_forward.experts.4.w3, model.layers.7.feed_forward.experts.5.w1,
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model.layers.7.feed_forward.experts.5.w3, model.layers.7.feed_forward.experts.6.w1,
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model.layers.7.feed_forward.experts.6.w3, model.layers.7.feed_forward.experts.7.w1,
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model.layers.7.feed_forward.experts.7.w3, model.layers.7.feed_forward.experts.8.w1,
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model.layers.7.feed_forward.experts.8.w3, model.layers.7.feed_forward.experts.9.w1,
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model.layers.7.feed_forward.experts.9.w3, model.layers.7.feed_forward.experts.10.w1,
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model.layers.7.feed_forward.experts.10.w3, model.layers.7.feed_forward.experts.11.w1,
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model.layers.7.feed_forward.experts.11.w3, model.layers.7.feed_forward.experts.12.w1,
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| 232 |
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model.layers.7.feed_forward.experts.12.w3, model.layers.7.feed_forward.experts.13.w1,
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| 233 |
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model.layers.7.feed_forward.experts.13.w3, model.layers.7.feed_forward.experts.14.w1,
|
| 234 |
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model.layers.7.feed_forward.experts.14.w3, model.layers.7.feed_forward.experts.15.w1,
|
| 235 |
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model.layers.7.feed_forward.experts.15.w3, model.layers.7.feed_forward.experts.16.w1,
|
| 236 |
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model.layers.7.feed_forward.experts.16.w3, model.layers.7.feed_forward.experts.17.w1,
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| 237 |
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model.layers.7.feed_forward.experts.17.w3, model.layers.7.feed_forward.experts.18.w1,
|
| 238 |
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model.layers.7.feed_forward.experts.18.w3, model.layers.7.feed_forward.experts.19.w1,
|
| 239 |
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model.layers.7.feed_forward.experts.19.w3, model.layers.7.feed_forward.experts.20.w1,
|
| 240 |
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model.layers.7.feed_forward.experts.20.w3, model.layers.7.feed_forward.experts.21.w1,
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| 241 |
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model.layers.7.feed_forward.experts.21.w3, model.layers.7.feed_forward.experts.22.w1,
|
| 242 |
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model.layers.7.feed_forward.experts.22.w3, model.layers.7.feed_forward.experts.23.w1,
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| 243 |
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model.layers.7.feed_forward.experts.23.w3, model.layers.7.feed_forward.experts.24.w1,
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| 244 |
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model.layers.7.feed_forward.experts.24.w3, model.layers.7.feed_forward.experts.25.w1,
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| 245 |
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model.layers.7.feed_forward.experts.25.w3, model.layers.7.feed_forward.experts.26.w1,
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| 246 |
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model.layers.7.feed_forward.experts.26.w3, model.layers.7.feed_forward.experts.27.w1,
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| 247 |
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model.layers.7.feed_forward.experts.27.w3, model.layers.7.feed_forward.experts.28.w1,
|
| 248 |
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model.layers.7.feed_forward.experts.28.w3, model.layers.7.feed_forward.experts.29.w1,
|
| 249 |
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model.layers.7.feed_forward.experts.29.w3, model.layers.7.feed_forward.experts.30.w1,
|
| 250 |
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model.layers.7.feed_forward.experts.30.w3, model.layers.7.feed_forward.experts.31.w1,
|
| 251 |
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model.layers.7.feed_forward.experts.31.w3]
|
| 252 |
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|
| 253 |
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balance_layers: [model.layers.8.conv.in_proj]
|
| 254 |
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|
| 255 |
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|
| 256 |
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model.layers.8.feed_forward.experts.0.w3, model.layers.8.feed_forward.experts.1.w1,
|
| 257 |
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model.layers.8.feed_forward.experts.1.w3, model.layers.8.feed_forward.experts.2.w1,
|
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model.layers.8.feed_forward.experts.2.w3, model.layers.8.feed_forward.experts.3.w1,
|
| 259 |
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model.layers.8.feed_forward.experts.3.w3, model.layers.8.feed_forward.experts.4.w1,
|
| 260 |
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model.layers.8.feed_forward.experts.4.w3, model.layers.8.feed_forward.experts.5.w1,
|
| 261 |
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model.layers.8.feed_forward.experts.5.w3, model.layers.8.feed_forward.experts.6.w1,
|
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model.layers.8.feed_forward.experts.6.w3, model.layers.8.feed_forward.experts.7.w1,
|
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model.layers.8.feed_forward.experts.7.w3, model.layers.8.feed_forward.experts.8.w1,
|
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model.layers.8.feed_forward.experts.8.w3, model.layers.8.feed_forward.experts.9.w1,
|
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model.layers.8.feed_forward.experts.9.w3, model.layers.8.feed_forward.experts.10.w1,
|
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model.layers.8.feed_forward.experts.10.w3, model.layers.8.feed_forward.experts.11.w1,
|
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model.layers.8.feed_forward.experts.11.w3, model.layers.8.feed_forward.experts.12.w1,
|
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model.layers.8.feed_forward.experts.12.w3, model.layers.8.feed_forward.experts.13.w1,
|
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model.layers.8.feed_forward.experts.13.w3, model.layers.8.feed_forward.experts.14.w1,
|
| 270 |
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model.layers.8.feed_forward.experts.14.w3, model.layers.8.feed_forward.experts.15.w1,
|
| 271 |
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model.layers.8.feed_forward.experts.15.w3, model.layers.8.feed_forward.experts.16.w1,
|
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model.layers.8.feed_forward.experts.16.w3, model.layers.8.feed_forward.experts.17.w1,
|
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model.layers.8.feed_forward.experts.17.w3, model.layers.8.feed_forward.experts.18.w1,
|
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model.layers.8.feed_forward.experts.18.w3, model.layers.8.feed_forward.experts.19.w1,
|
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model.layers.8.feed_forward.experts.19.w3, model.layers.8.feed_forward.experts.20.w1,
|
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model.layers.8.feed_forward.experts.20.w3, model.layers.8.feed_forward.experts.21.w1,
|
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model.layers.8.feed_forward.experts.21.w3, model.layers.8.feed_forward.experts.22.w1,
|
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model.layers.8.feed_forward.experts.22.w3, model.layers.8.feed_forward.experts.23.w1,
|
| 279 |
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model.layers.8.feed_forward.experts.23.w3, model.layers.8.feed_forward.experts.24.w1,
|
| 280 |
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model.layers.8.feed_forward.experts.24.w3, model.layers.8.feed_forward.experts.25.w1,
|
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model.layers.8.feed_forward.experts.25.w3, model.layers.8.feed_forward.experts.26.w1,
|
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model.layers.8.feed_forward.experts.26.w3, model.layers.8.feed_forward.experts.27.w1,
|
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model.layers.8.feed_forward.experts.27.w3, model.layers.8.feed_forward.experts.28.w1,
|
| 284 |
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model.layers.8.feed_forward.experts.28.w3, model.layers.8.feed_forward.experts.29.w1,
|
| 285 |
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model.layers.8.feed_forward.experts.29.w3, model.layers.8.feed_forward.experts.30.w1,
|
| 286 |
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model.layers.8.feed_forward.experts.30.w3, model.layers.8.feed_forward.experts.31.w1,
|
| 287 |
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model.layers.8.feed_forward.experts.31.w3]
|
| 288 |
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|
| 289 |
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|
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|
| 291 |
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|
| 292 |
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model.layers.9.feed_forward.experts.0.w3, model.layers.9.feed_forward.experts.1.w1,
|
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model.layers.9.feed_forward.experts.1.w3, model.layers.9.feed_forward.experts.2.w1,
|
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model.layers.9.feed_forward.experts.2.w3, model.layers.9.feed_forward.experts.3.w1,
|
| 295 |
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model.layers.9.feed_forward.experts.3.w3, model.layers.9.feed_forward.experts.4.w1,
|
| 296 |
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model.layers.9.feed_forward.experts.4.w3, model.layers.9.feed_forward.experts.5.w1,
|
| 297 |
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model.layers.9.feed_forward.experts.5.w3, model.layers.9.feed_forward.experts.6.w1,
|
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model.layers.9.feed_forward.experts.6.w3, model.layers.9.feed_forward.experts.7.w1,
|
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model.layers.9.feed_forward.experts.7.w3, model.layers.9.feed_forward.experts.8.w1,
|
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model.layers.9.feed_forward.experts.8.w3, model.layers.9.feed_forward.experts.9.w1,
|
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model.layers.9.feed_forward.experts.9.w3, model.layers.9.feed_forward.experts.10.w1,
|
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model.layers.9.feed_forward.experts.10.w3, model.layers.9.feed_forward.experts.11.w1,
|
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model.layers.9.feed_forward.experts.11.w3, model.layers.9.feed_forward.experts.12.w1,
|
| 304 |
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model.layers.9.feed_forward.experts.12.w3, model.layers.9.feed_forward.experts.13.w1,
|
| 305 |
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model.layers.9.feed_forward.experts.13.w3, model.layers.9.feed_forward.experts.14.w1,
|
| 306 |
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model.layers.9.feed_forward.experts.14.w3, model.layers.9.feed_forward.experts.15.w1,
|
| 307 |
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model.layers.9.feed_forward.experts.15.w3, model.layers.9.feed_forward.experts.16.w1,
|
| 308 |
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model.layers.9.feed_forward.experts.16.w3, model.layers.9.feed_forward.experts.17.w1,
|
| 309 |
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model.layers.9.feed_forward.experts.17.w3, model.layers.9.feed_forward.experts.18.w1,
|
| 310 |
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model.layers.9.feed_forward.experts.18.w3, model.layers.9.feed_forward.experts.19.w1,
|
| 311 |
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model.layers.9.feed_forward.experts.19.w3, model.layers.9.feed_forward.experts.20.w1,
|
| 312 |
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model.layers.9.feed_forward.experts.20.w3, model.layers.9.feed_forward.experts.21.w1,
|
| 313 |
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model.layers.9.feed_forward.experts.21.w3, model.layers.9.feed_forward.experts.22.w1,
|
| 314 |
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model.layers.9.feed_forward.experts.22.w3, model.layers.9.feed_forward.experts.23.w1,
|
| 315 |
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model.layers.9.feed_forward.experts.23.w3, model.layers.9.feed_forward.experts.24.w1,
|
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model.layers.9.feed_forward.experts.24.w3, model.layers.9.feed_forward.experts.25.w1,
|
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model.layers.9.feed_forward.experts.25.w3, model.layers.9.feed_forward.experts.26.w1,
|
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model.layers.9.feed_forward.experts.26.w3, model.layers.9.feed_forward.experts.27.w1,
|
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model.layers.9.feed_forward.experts.27.w3, model.layers.9.feed_forward.experts.28.w1,
|
| 320 |
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model.layers.9.feed_forward.experts.28.w3, model.layers.9.feed_forward.experts.29.w1,
|
| 321 |
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model.layers.9.feed_forward.experts.29.w3, model.layers.9.feed_forward.experts.30.w1,
|
| 322 |
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model.layers.9.feed_forward.experts.30.w3, model.layers.9.feed_forward.experts.31.w1,
|
| 323 |
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model.layers.9.feed_forward.experts.31.w3]
|
| 324 |
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|
| 325 |
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balance_layers: [model.layers.10.self_attn.q_proj, model.layers.10.self_attn.k_proj,
|
| 326 |
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model.layers.10.self_attn.v_proj]
|
| 327 |
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|
| 328 |
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balance_layers: [model.layers.10.feed_forward.gate, model.layers.10.feed_forward.experts.0.w1,
|
| 329 |
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model.layers.10.feed_forward.experts.0.w3, model.layers.10.feed_forward.experts.1.w1,
|
| 330 |
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model.layers.10.feed_forward.experts.1.w3, model.layers.10.feed_forward.experts.2.w1,
|
| 331 |
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model.layers.10.feed_forward.experts.2.w3, model.layers.10.feed_forward.experts.3.w1,
|
| 332 |
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model.layers.10.feed_forward.experts.3.w3, model.layers.10.feed_forward.experts.4.w1,
|
| 333 |
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model.layers.10.feed_forward.experts.4.w3, model.layers.10.feed_forward.experts.5.w1,
|
| 334 |
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model.layers.10.feed_forward.experts.5.w3, model.layers.10.feed_forward.experts.6.w1,
|
| 335 |
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model.layers.10.feed_forward.experts.6.w3, model.layers.10.feed_forward.experts.7.w1,
|
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model.layers.10.feed_forward.experts.7.w3, model.layers.10.feed_forward.experts.8.w1,
|
| 337 |
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model.layers.10.feed_forward.experts.8.w3, model.layers.10.feed_forward.experts.9.w1,
|
| 338 |
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model.layers.10.feed_forward.experts.9.w3, model.layers.10.feed_forward.experts.10.w1,
|
| 339 |
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model.layers.10.feed_forward.experts.10.w3, model.layers.10.feed_forward.experts.11.w1,
|
| 340 |
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model.layers.10.feed_forward.experts.11.w3, model.layers.10.feed_forward.experts.12.w1,
|
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model.layers.10.feed_forward.experts.12.w3, model.layers.10.feed_forward.experts.13.w1,
|
| 342 |
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model.layers.10.feed_forward.experts.13.w3, model.layers.10.feed_forward.experts.14.w1,
|
| 343 |
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model.layers.10.feed_forward.experts.14.w3, model.layers.10.feed_forward.experts.15.w1,
|
| 344 |
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model.layers.10.feed_forward.experts.15.w3, model.layers.10.feed_forward.experts.16.w1,
|
| 345 |
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model.layers.10.feed_forward.experts.16.w3, model.layers.10.feed_forward.experts.17.w1,
|
| 346 |
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model.layers.10.feed_forward.experts.17.w3, model.layers.10.feed_forward.experts.18.w1,
|
| 347 |
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model.layers.10.feed_forward.experts.18.w3, model.layers.10.feed_forward.experts.19.w1,
|
| 348 |
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model.layers.10.feed_forward.experts.19.w3, model.layers.10.feed_forward.experts.20.w1,
|
| 349 |
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model.layers.10.feed_forward.experts.20.w3, model.layers.10.feed_forward.experts.21.w1,
|
| 350 |
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model.layers.10.feed_forward.experts.21.w3, model.layers.10.feed_forward.experts.22.w1,
|
| 351 |
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model.layers.10.feed_forward.experts.22.w3, model.layers.10.feed_forward.experts.23.w1,
|
| 352 |
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model.layers.10.feed_forward.experts.23.w3, model.layers.10.feed_forward.experts.24.w1,
|
| 353 |
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model.layers.10.feed_forward.experts.24.w3, model.layers.10.feed_forward.experts.25.w1,
|
| 354 |
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model.layers.10.feed_forward.experts.25.w3, model.layers.10.feed_forward.experts.26.w1,
|
| 355 |
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model.layers.10.feed_forward.experts.26.w3, model.layers.10.feed_forward.experts.27.w1,
|
| 356 |
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model.layers.10.feed_forward.experts.27.w3, model.layers.10.feed_forward.experts.28.w1,
|
| 357 |
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model.layers.10.feed_forward.experts.28.w3, model.layers.10.feed_forward.experts.29.w1,
|
| 358 |
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model.layers.10.feed_forward.experts.29.w3, model.layers.10.feed_forward.experts.30.w1,
|
| 359 |
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model.layers.10.feed_forward.experts.30.w3, model.layers.10.feed_forward.experts.31.w1,
|
| 360 |
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model.layers.10.feed_forward.experts.31.w3]
|
| 361 |
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|
| 362 |
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balance_layers: [model.layers.11.conv.in_proj]
|
| 363 |
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|
| 364 |
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balance_layers: [model.layers.11.feed_forward.gate, model.layers.11.feed_forward.experts.0.w1,
|
| 365 |
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model.layers.11.feed_forward.experts.0.w3, model.layers.11.feed_forward.experts.1.w1,
|
| 366 |
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model.layers.11.feed_forward.experts.1.w3, model.layers.11.feed_forward.experts.2.w1,
|
| 367 |
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model.layers.11.feed_forward.experts.2.w3, model.layers.11.feed_forward.experts.3.w1,
|
| 368 |
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model.layers.11.feed_forward.experts.3.w3, model.layers.11.feed_forward.experts.4.w1,
|
| 369 |
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model.layers.11.feed_forward.experts.4.w3, model.layers.11.feed_forward.experts.5.w1,
|
| 370 |
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model.layers.11.feed_forward.experts.5.w3, model.layers.11.feed_forward.experts.6.w1,
|
| 371 |
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model.layers.11.feed_forward.experts.6.w3, model.layers.11.feed_forward.experts.7.w1,
|
| 372 |
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model.layers.11.feed_forward.experts.7.w3, model.layers.11.feed_forward.experts.8.w1,
|
| 373 |
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model.layers.11.feed_forward.experts.8.w3, model.layers.11.feed_forward.experts.9.w1,
|
| 374 |
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model.layers.11.feed_forward.experts.9.w3, model.layers.11.feed_forward.experts.10.w1,
|
| 375 |
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model.layers.11.feed_forward.experts.10.w3, model.layers.11.feed_forward.experts.11.w1,
|
| 376 |
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model.layers.11.feed_forward.experts.11.w3, model.layers.11.feed_forward.experts.12.w1,
|
| 377 |
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model.layers.11.feed_forward.experts.12.w3, model.layers.11.feed_forward.experts.13.w1,
|
| 378 |
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model.layers.11.feed_forward.experts.13.w3, model.layers.11.feed_forward.experts.14.w1,
|
| 379 |
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model.layers.11.feed_forward.experts.14.w3, model.layers.11.feed_forward.experts.15.w1,
|
| 380 |
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model.layers.11.feed_forward.experts.15.w3, model.layers.11.feed_forward.experts.16.w1,
|
| 381 |
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model.layers.11.feed_forward.experts.16.w3, model.layers.11.feed_forward.experts.17.w1,
|
| 382 |
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model.layers.11.feed_forward.experts.17.w3, model.layers.11.feed_forward.experts.18.w1,
|
| 383 |
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model.layers.11.feed_forward.experts.18.w3, model.layers.11.feed_forward.experts.19.w1,
|
| 384 |
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model.layers.11.feed_forward.experts.19.w3, model.layers.11.feed_forward.experts.20.w1,
|
| 385 |
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model.layers.11.feed_forward.experts.20.w3, model.layers.11.feed_forward.experts.21.w1,
|
| 386 |
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model.layers.11.feed_forward.experts.21.w3, model.layers.11.feed_forward.experts.22.w1,
|
| 387 |
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model.layers.11.feed_forward.experts.22.w3, model.layers.11.feed_forward.experts.23.w1,
|
| 388 |
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model.layers.11.feed_forward.experts.23.w3, model.layers.11.feed_forward.experts.24.w1,
|
| 389 |
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model.layers.11.feed_forward.experts.24.w3, model.layers.11.feed_forward.experts.25.w1,
|
| 390 |
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model.layers.11.feed_forward.experts.25.w3, model.layers.11.feed_forward.experts.26.w1,
|
| 391 |
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model.layers.11.feed_forward.experts.26.w3, model.layers.11.feed_forward.experts.27.w1,
|
| 392 |
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model.layers.11.feed_forward.experts.27.w3, model.layers.11.feed_forward.experts.28.w1,
|
| 393 |
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model.layers.11.feed_forward.experts.28.w3, model.layers.11.feed_forward.experts.29.w1,
|
| 394 |
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model.layers.11.feed_forward.experts.29.w3, model.layers.11.feed_forward.experts.30.w1,
|
| 395 |
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model.layers.11.feed_forward.experts.30.w3, model.layers.11.feed_forward.experts.31.w1,
|
| 396 |
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model.layers.11.feed_forward.experts.31.w3]
|
| 397 |
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|
| 398 |
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balance_layers: [model.layers.12.conv.in_proj]
|
| 399 |
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|
| 400 |
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balance_layers: [model.layers.12.feed_forward.gate, model.layers.12.feed_forward.experts.0.w1,
|
| 401 |
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model.layers.12.feed_forward.experts.0.w3, model.layers.12.feed_forward.experts.1.w1,
|
| 402 |
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model.layers.12.feed_forward.experts.1.w3, model.layers.12.feed_forward.experts.2.w1,
|
| 403 |
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model.layers.12.feed_forward.experts.2.w3, model.layers.12.feed_forward.experts.3.w1,
|
| 404 |
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model.layers.12.feed_forward.experts.3.w3, model.layers.12.feed_forward.experts.4.w1,
|
| 405 |
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model.layers.12.feed_forward.experts.4.w3, model.layers.12.feed_forward.experts.5.w1,
|
| 406 |
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model.layers.12.feed_forward.experts.5.w3, model.layers.12.feed_forward.experts.6.w1,
|
| 407 |
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model.layers.12.feed_forward.experts.6.w3, model.layers.12.feed_forward.experts.7.w1,
|
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model.layers.12.feed_forward.experts.7.w3, model.layers.12.feed_forward.experts.8.w1,
|
| 409 |
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model.layers.12.feed_forward.experts.8.w3, model.layers.12.feed_forward.experts.9.w1,
|
| 410 |
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model.layers.12.feed_forward.experts.9.w3, model.layers.12.feed_forward.experts.10.w1,
|
| 411 |
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model.layers.12.feed_forward.experts.10.w3, model.layers.12.feed_forward.experts.11.w1,
|
| 412 |
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model.layers.12.feed_forward.experts.11.w3, model.layers.12.feed_forward.experts.12.w1,
|
| 413 |
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model.layers.12.feed_forward.experts.12.w3, model.layers.12.feed_forward.experts.13.w1,
|
| 414 |
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model.layers.12.feed_forward.experts.13.w3, model.layers.12.feed_forward.experts.14.w1,
|
| 415 |
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model.layers.12.feed_forward.experts.14.w3, model.layers.12.feed_forward.experts.15.w1,
|
| 416 |
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model.layers.12.feed_forward.experts.15.w3, model.layers.12.feed_forward.experts.16.w1,
|
| 417 |
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model.layers.12.feed_forward.experts.16.w3, model.layers.12.feed_forward.experts.17.w1,
|
| 418 |
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model.layers.12.feed_forward.experts.17.w3, model.layers.12.feed_forward.experts.18.w1,
|
| 419 |
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model.layers.12.feed_forward.experts.18.w3, model.layers.12.feed_forward.experts.19.w1,
|
| 420 |
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model.layers.12.feed_forward.experts.19.w3, model.layers.12.feed_forward.experts.20.w1,
|
| 421 |
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model.layers.12.feed_forward.experts.20.w3, model.layers.12.feed_forward.experts.21.w1,
|
| 422 |
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model.layers.12.feed_forward.experts.21.w3, model.layers.12.feed_forward.experts.22.w1,
|
| 423 |
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model.layers.12.feed_forward.experts.22.w3, model.layers.12.feed_forward.experts.23.w1,
|
| 424 |
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model.layers.12.feed_forward.experts.23.w3, model.layers.12.feed_forward.experts.24.w1,
|
| 425 |
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model.layers.12.feed_forward.experts.24.w3, model.layers.12.feed_forward.experts.25.w1,
|
| 426 |
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model.layers.12.feed_forward.experts.25.w3, model.layers.12.feed_forward.experts.26.w1,
|
| 427 |
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model.layers.13.feed_forward.experts.31.w3]
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model.layers.14.self_attn.v_proj]
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model.layers.14.feed_forward.experts.3.w3, model.layers.14.feed_forward.experts.4.w1,
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model.layers.14.feed_forward.experts.4.w3, model.layers.14.feed_forward.experts.5.w1,
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model.layers.14.feed_forward.experts.9.w3, model.layers.14.feed_forward.experts.10.w1,
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model.layers.14.feed_forward.experts.10.w3, model.layers.14.feed_forward.experts.11.w1,
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model.layers.14.feed_forward.experts.12.w3, model.layers.14.feed_forward.experts.13.w1,
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model.layers.14.feed_forward.experts.13.w3, model.layers.14.feed_forward.experts.14.w1,
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|
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| 558 |
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model.layers.16.feed_forward.experts.12.w3, model.layers.16.feed_forward.experts.13.w1,
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model.layers.16.feed_forward.experts.13.w3, model.layers.16.feed_forward.experts.14.w1,
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model.layers.16.feed_forward.experts.14.w3, model.layers.16.feed_forward.experts.15.w1,
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model.layers.16.feed_forward.experts.15.w3, model.layers.16.feed_forward.experts.16.w1,
|
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model.layers.16.feed_forward.experts.16.w3, model.layers.16.feed_forward.experts.17.w1,
|
| 563 |
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model.layers.16.feed_forward.experts.17.w3, model.layers.16.feed_forward.experts.18.w1,
|
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model.layers.16.feed_forward.experts.18.w3, model.layers.16.feed_forward.experts.19.w1,
|
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model.layers.16.feed_forward.experts.19.w3, model.layers.16.feed_forward.experts.20.w1,
|
| 566 |
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model.layers.16.feed_forward.experts.20.w3, model.layers.16.feed_forward.experts.21.w1,
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model.layers.16.feed_forward.experts.21.w3, model.layers.16.feed_forward.experts.22.w1,
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model.layers.16.feed_forward.experts.22.w3, model.layers.16.feed_forward.experts.23.w1,
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|
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model.layers.16.feed_forward.experts.24.w3, model.layers.16.feed_forward.experts.25.w1,
|
| 571 |
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model.layers.16.feed_forward.experts.25.w3, model.layers.16.feed_forward.experts.26.w1,
|
| 572 |
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model.layers.16.feed_forward.experts.26.w3, model.layers.16.feed_forward.experts.27.w1,
|
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model.layers.16.feed_forward.experts.27.w3, model.layers.16.feed_forward.experts.28.w1,
|
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model.layers.16.feed_forward.experts.28.w3, model.layers.16.feed_forward.experts.29.w1,
|
| 575 |
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model.layers.16.feed_forward.experts.29.w3, model.layers.16.feed_forward.experts.30.w1,
|
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model.layers.16.feed_forward.experts.30.w3, model.layers.16.feed_forward.experts.31.w1,
|
| 577 |
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model.layers.16.feed_forward.experts.31.w3]
|
| 578 |
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|
| 579 |
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|
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|
| 581 |
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|
| 582 |
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model.layers.17.feed_forward.experts.0.w3, model.layers.17.feed_forward.experts.1.w1,
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model.layers.17.feed_forward.experts.1.w3, model.layers.17.feed_forward.experts.2.w1,
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| 584 |
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model.layers.17.feed_forward.experts.2.w3, model.layers.17.feed_forward.experts.3.w1,
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| 585 |
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model.layers.17.feed_forward.experts.3.w3, model.layers.17.feed_forward.experts.4.w1,
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|
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model.layers.17.feed_forward.experts.5.w3, model.layers.17.feed_forward.experts.6.w1,
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model.layers.17.feed_forward.experts.6.w3, model.layers.17.feed_forward.experts.7.w1,
|
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model.layers.17.feed_forward.experts.7.w3, model.layers.17.feed_forward.experts.8.w1,
|
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|
| 591 |
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|
| 592 |
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|
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model.layers.17.feed_forward.experts.12.w3, model.layers.17.feed_forward.experts.13.w1,
|
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model.layers.17.feed_forward.experts.13.w3, model.layers.17.feed_forward.experts.14.w1,
|
| 596 |
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model.layers.17.feed_forward.experts.14.w3, model.layers.17.feed_forward.experts.15.w1,
|
| 597 |
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model.layers.17.feed_forward.experts.15.w3, model.layers.17.feed_forward.experts.16.w1,
|
| 598 |
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model.layers.17.feed_forward.experts.16.w3, model.layers.17.feed_forward.experts.17.w1,
|
| 599 |
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model.layers.17.feed_forward.experts.17.w3, model.layers.17.feed_forward.experts.18.w1,
|
| 600 |
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model.layers.17.feed_forward.experts.18.w3, model.layers.17.feed_forward.experts.19.w1,
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| 601 |
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model.layers.17.feed_forward.experts.19.w3, model.layers.17.feed_forward.experts.20.w1,
|
| 602 |
+
model.layers.17.feed_forward.experts.20.w3, model.layers.17.feed_forward.experts.21.w1,
|
| 603 |
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model.layers.17.feed_forward.experts.21.w3, model.layers.17.feed_forward.experts.22.w1,
|
| 604 |
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model.layers.17.feed_forward.experts.22.w3, model.layers.17.feed_forward.experts.23.w1,
|
| 605 |
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model.layers.17.feed_forward.experts.23.w3, model.layers.17.feed_forward.experts.24.w1,
|
| 606 |
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model.layers.17.feed_forward.experts.24.w3, model.layers.17.feed_forward.experts.25.w1,
|
| 607 |
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model.layers.17.feed_forward.experts.25.w3, model.layers.17.feed_forward.experts.26.w1,
|
| 608 |
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model.layers.17.feed_forward.experts.26.w3, model.layers.17.feed_forward.experts.27.w1,
|
| 609 |
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model.layers.17.feed_forward.experts.27.w3, model.layers.17.feed_forward.experts.28.w1,
|
| 610 |
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model.layers.17.feed_forward.experts.28.w3, model.layers.17.feed_forward.experts.29.w1,
|
| 611 |
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model.layers.17.feed_forward.experts.29.w3, model.layers.17.feed_forward.experts.30.w1,
|
| 612 |
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model.layers.17.feed_forward.experts.30.w3, model.layers.17.feed_forward.experts.31.w1,
|
| 613 |
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model.layers.17.feed_forward.experts.31.w3]
|
| 614 |
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|
| 615 |
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balance_layers: [model.layers.18.self_attn.q_proj, model.layers.18.self_attn.k_proj,
|
| 616 |
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model.layers.18.self_attn.v_proj]
|
| 617 |
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|
| 618 |
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balance_layers: [model.layers.18.feed_forward.gate, model.layers.18.feed_forward.experts.0.w1,
|
| 619 |
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model.layers.18.feed_forward.experts.0.w3, model.layers.18.feed_forward.experts.1.w1,
|
| 620 |
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model.layers.18.feed_forward.experts.1.w3, model.layers.18.feed_forward.experts.2.w1,
|
| 621 |
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model.layers.18.feed_forward.experts.2.w3, model.layers.18.feed_forward.experts.3.w1,
|
| 622 |
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model.layers.18.feed_forward.experts.3.w3, model.layers.18.feed_forward.experts.4.w1,
|
| 623 |
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model.layers.18.feed_forward.experts.4.w3, model.layers.18.feed_forward.experts.5.w1,
|
| 624 |
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model.layers.18.feed_forward.experts.5.w3, model.layers.18.feed_forward.experts.6.w1,
|
| 625 |
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model.layers.18.feed_forward.experts.6.w3, model.layers.18.feed_forward.experts.7.w1,
|
| 626 |
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model.layers.18.feed_forward.experts.7.w3, model.layers.18.feed_forward.experts.8.w1,
|
| 627 |
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model.layers.18.feed_forward.experts.8.w3, model.layers.18.feed_forward.experts.9.w1,
|
| 628 |
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model.layers.18.feed_forward.experts.9.w3, model.layers.18.feed_forward.experts.10.w1,
|
| 629 |
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model.layers.18.feed_forward.experts.10.w3, model.layers.18.feed_forward.experts.11.w1,
|
| 630 |
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model.layers.18.feed_forward.experts.11.w3, model.layers.18.feed_forward.experts.12.w1,
|
| 631 |
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model.layers.18.feed_forward.experts.12.w3, model.layers.18.feed_forward.experts.13.w1,
|
| 632 |
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model.layers.18.feed_forward.experts.13.w3, model.layers.18.feed_forward.experts.14.w1,
|
| 633 |
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model.layers.18.feed_forward.experts.14.w3, model.layers.18.feed_forward.experts.15.w1,
|
| 634 |
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model.layers.18.feed_forward.experts.15.w3, model.layers.18.feed_forward.experts.16.w1,
|
| 635 |
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model.layers.18.feed_forward.experts.16.w3, model.layers.18.feed_forward.experts.17.w1,
|
| 636 |
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model.layers.18.feed_forward.experts.17.w3, model.layers.18.feed_forward.experts.18.w1,
|
| 637 |
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model.layers.18.feed_forward.experts.18.w3, model.layers.18.feed_forward.experts.19.w1,
|
| 638 |
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model.layers.18.feed_forward.experts.19.w3, model.layers.18.feed_forward.experts.20.w1,
|
| 639 |
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model.layers.18.feed_forward.experts.20.w3, model.layers.18.feed_forward.experts.21.w1,
|
| 640 |
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model.layers.18.feed_forward.experts.21.w3, model.layers.18.feed_forward.experts.22.w1,
|
| 641 |
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model.layers.18.feed_forward.experts.22.w3, model.layers.18.feed_forward.experts.23.w1,
|
| 642 |
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model.layers.18.feed_forward.experts.23.w3, model.layers.18.feed_forward.experts.24.w1,
|
| 643 |
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model.layers.18.feed_forward.experts.24.w3, model.layers.18.feed_forward.experts.25.w1,
|
| 644 |
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model.layers.18.feed_forward.experts.25.w3, model.layers.18.feed_forward.experts.26.w1,
|
| 645 |
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model.layers.18.feed_forward.experts.26.w3, model.layers.18.feed_forward.experts.27.w1,
|
| 646 |
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model.layers.18.feed_forward.experts.27.w3, model.layers.18.feed_forward.experts.28.w1,
|
| 647 |
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model.layers.18.feed_forward.experts.28.w3, model.layers.18.feed_forward.experts.29.w1,
|
| 648 |
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model.layers.18.feed_forward.experts.29.w3, model.layers.18.feed_forward.experts.30.w1,
|
| 649 |
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model.layers.18.feed_forward.experts.30.w3, model.layers.18.feed_forward.experts.31.w1,
|
| 650 |
+
model.layers.18.feed_forward.experts.31.w3]
|
| 651 |
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|
| 652 |
+
balance_layers: [model.layers.19.conv.in_proj]
|
| 653 |
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|
| 654 |
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balance_layers: [model.layers.19.feed_forward.gate, model.layers.19.feed_forward.experts.0.w1,
|
| 655 |
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model.layers.19.feed_forward.experts.0.w3, model.layers.19.feed_forward.experts.1.w1,
|
| 656 |
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model.layers.19.feed_forward.experts.1.w3, model.layers.19.feed_forward.experts.2.w1,
|
| 657 |
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model.layers.19.feed_forward.experts.2.w3, model.layers.19.feed_forward.experts.3.w1,
|
| 658 |
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model.layers.19.feed_forward.experts.3.w3, model.layers.19.feed_forward.experts.4.w1,
|
| 659 |
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model.layers.19.feed_forward.experts.4.w3, model.layers.19.feed_forward.experts.5.w1,
|
| 660 |
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model.layers.19.feed_forward.experts.5.w3, model.layers.19.feed_forward.experts.6.w1,
|
| 661 |
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model.layers.19.feed_forward.experts.6.w3, model.layers.19.feed_forward.experts.7.w1,
|
| 662 |
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model.layers.19.feed_forward.experts.7.w3, model.layers.19.feed_forward.experts.8.w1,
|
| 663 |
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model.layers.19.feed_forward.experts.8.w3, model.layers.19.feed_forward.experts.9.w1,
|
| 664 |
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model.layers.19.feed_forward.experts.9.w3, model.layers.19.feed_forward.experts.10.w1,
|
| 665 |
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model.layers.19.feed_forward.experts.10.w3, model.layers.19.feed_forward.experts.11.w1,
|
| 666 |
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model.layers.19.feed_forward.experts.11.w3, model.layers.19.feed_forward.experts.12.w1,
|
| 667 |
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model.layers.19.feed_forward.experts.12.w3, model.layers.19.feed_forward.experts.13.w1,
|
| 668 |
+
model.layers.19.feed_forward.experts.13.w3, model.layers.19.feed_forward.experts.14.w1,
|
| 669 |
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model.layers.19.feed_forward.experts.14.w3, model.layers.19.feed_forward.experts.15.w1,
|
| 670 |
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model.layers.19.feed_forward.experts.15.w3, model.layers.19.feed_forward.experts.16.w1,
|
| 671 |
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model.layers.19.feed_forward.experts.16.w3, model.layers.19.feed_forward.experts.17.w1,
|
| 672 |
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model.layers.19.feed_forward.experts.17.w3, model.layers.19.feed_forward.experts.18.w1,
|
| 673 |
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model.layers.19.feed_forward.experts.18.w3, model.layers.19.feed_forward.experts.19.w1,
|
| 674 |
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model.layers.19.feed_forward.experts.19.w3, model.layers.19.feed_forward.experts.20.w1,
|
| 675 |
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model.layers.19.feed_forward.experts.20.w3, model.layers.19.feed_forward.experts.21.w1,
|
| 676 |
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model.layers.19.feed_forward.experts.21.w3, model.layers.19.feed_forward.experts.22.w1,
|
| 677 |
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model.layers.19.feed_forward.experts.22.w3, model.layers.19.feed_forward.experts.23.w1,
|
| 678 |
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model.layers.19.feed_forward.experts.23.w3, model.layers.19.feed_forward.experts.24.w1,
|
| 679 |
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model.layers.19.feed_forward.experts.24.w3, model.layers.19.feed_forward.experts.25.w1,
|
| 680 |
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model.layers.19.feed_forward.experts.25.w3, model.layers.19.feed_forward.experts.26.w1,
|
| 681 |
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model.layers.19.feed_forward.experts.26.w3, model.layers.19.feed_forward.experts.27.w1,
|
| 682 |
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model.layers.19.feed_forward.experts.27.w3, model.layers.19.feed_forward.experts.28.w1,
|
| 683 |
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model.layers.19.feed_forward.experts.28.w3, model.layers.19.feed_forward.experts.29.w1,
|
| 684 |
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model.layers.19.feed_forward.experts.29.w3, model.layers.19.feed_forward.experts.30.w1,
|
| 685 |
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model.layers.19.feed_forward.experts.30.w3, model.layers.19.feed_forward.experts.31.w1,
|
| 686 |
+
model.layers.19.feed_forward.experts.31.w3]
|
| 687 |
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|
| 688 |
+
balance_layers: [model.layers.20.conv.in_proj]
|
| 689 |
+
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|
| 690 |
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balance_layers: [model.layers.20.feed_forward.gate, model.layers.20.feed_forward.experts.0.w1,
|
| 691 |
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model.layers.20.feed_forward.experts.0.w3, model.layers.20.feed_forward.experts.1.w1,
|
| 692 |
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model.layers.20.feed_forward.experts.1.w3, model.layers.20.feed_forward.experts.2.w1,
|
| 693 |
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model.layers.20.feed_forward.experts.2.w3, model.layers.20.feed_forward.experts.3.w1,
|
| 694 |
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model.layers.20.feed_forward.experts.3.w3, model.layers.20.feed_forward.experts.4.w1,
|
| 695 |
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model.layers.20.feed_forward.experts.4.w3, model.layers.20.feed_forward.experts.5.w1,
|
| 696 |
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model.layers.20.feed_forward.experts.5.w3, model.layers.20.feed_forward.experts.6.w1,
|
| 697 |
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model.layers.20.feed_forward.experts.6.w3, model.layers.20.feed_forward.experts.7.w1,
|
| 698 |
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model.layers.20.feed_forward.experts.7.w3, model.layers.20.feed_forward.experts.8.w1,
|
| 699 |
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model.layers.20.feed_forward.experts.8.w3, model.layers.20.feed_forward.experts.9.w1,
|
| 700 |
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model.layers.20.feed_forward.experts.9.w3, model.layers.20.feed_forward.experts.10.w1,
|
| 701 |
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model.layers.20.feed_forward.experts.10.w3, model.layers.20.feed_forward.experts.11.w1,
|
| 702 |
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model.layers.20.feed_forward.experts.11.w3, model.layers.20.feed_forward.experts.12.w1,
|
| 703 |
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model.layers.20.feed_forward.experts.12.w3, model.layers.20.feed_forward.experts.13.w1,
|
| 704 |
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model.layers.20.feed_forward.experts.13.w3, model.layers.20.feed_forward.experts.14.w1,
|
| 705 |
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model.layers.20.feed_forward.experts.14.w3, model.layers.20.feed_forward.experts.15.w1,
|
| 706 |
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model.layers.20.feed_forward.experts.15.w3, model.layers.20.feed_forward.experts.16.w1,
|
| 707 |
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model.layers.20.feed_forward.experts.16.w3, model.layers.20.feed_forward.experts.17.w1,
|
| 708 |
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model.layers.20.feed_forward.experts.17.w3, model.layers.20.feed_forward.experts.18.w1,
|
| 709 |
+
model.layers.20.feed_forward.experts.18.w3, model.layers.20.feed_forward.experts.19.w1,
|
| 710 |
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model.layers.20.feed_forward.experts.19.w3, model.layers.20.feed_forward.experts.20.w1,
|
| 711 |
+
model.layers.20.feed_forward.experts.20.w3, model.layers.20.feed_forward.experts.21.w1,
|
| 712 |
+
model.layers.20.feed_forward.experts.21.w3, model.layers.20.feed_forward.experts.22.w1,
|
| 713 |
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model.layers.20.feed_forward.experts.22.w3, model.layers.20.feed_forward.experts.23.w1,
|
| 714 |
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model.layers.20.feed_forward.experts.23.w3, model.layers.20.feed_forward.experts.24.w1,
|
| 715 |
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model.layers.20.feed_forward.experts.24.w3, model.layers.20.feed_forward.experts.25.w1,
|
| 716 |
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model.layers.20.feed_forward.experts.25.w3, model.layers.20.feed_forward.experts.26.w1,
|
| 717 |
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model.layers.20.feed_forward.experts.26.w3, model.layers.20.feed_forward.experts.27.w1,
|
| 718 |
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model.layers.20.feed_forward.experts.27.w3, model.layers.20.feed_forward.experts.28.w1,
|
| 719 |
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model.layers.20.feed_forward.experts.28.w3, model.layers.20.feed_forward.experts.29.w1,
|
| 720 |
+
model.layers.20.feed_forward.experts.29.w3, model.layers.20.feed_forward.experts.30.w1,
|
| 721 |
+
model.layers.20.feed_forward.experts.30.w3, model.layers.20.feed_forward.experts.31.w1,
|
| 722 |
+
model.layers.20.feed_forward.experts.31.w3]
|
| 723 |
+
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|
| 724 |
+
balance_layers: [model.layers.21.self_attn.q_proj, model.layers.21.self_attn.k_proj,
|
| 725 |
+
model.layers.21.self_attn.v_proj]
|
| 726 |
+
- smooth_layer: model.layers.21.ffn_norm
|
| 727 |
+
balance_layers: [model.layers.21.feed_forward.gate, model.layers.21.feed_forward.experts.0.w1,
|
| 728 |
+
model.layers.21.feed_forward.experts.0.w3, model.layers.21.feed_forward.experts.1.w1,
|
| 729 |
+
model.layers.21.feed_forward.experts.1.w3, model.layers.21.feed_forward.experts.2.w1,
|
| 730 |
+
model.layers.21.feed_forward.experts.2.w3, model.layers.21.feed_forward.experts.3.w1,
|
| 731 |
+
model.layers.21.feed_forward.experts.3.w3, model.layers.21.feed_forward.experts.4.w1,
|
| 732 |
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model.layers.21.feed_forward.experts.4.w3, model.layers.21.feed_forward.experts.5.w1,
|
| 733 |
+
model.layers.21.feed_forward.experts.5.w3, model.layers.21.feed_forward.experts.6.w1,
|
| 734 |
+
model.layers.21.feed_forward.experts.6.w3, model.layers.21.feed_forward.experts.7.w1,
|
| 735 |
+
model.layers.21.feed_forward.experts.7.w3, model.layers.21.feed_forward.experts.8.w1,
|
| 736 |
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model.layers.21.feed_forward.experts.8.w3, model.layers.21.feed_forward.experts.9.w1,
|
| 737 |
+
model.layers.21.feed_forward.experts.9.w3, model.layers.21.feed_forward.experts.10.w1,
|
| 738 |
+
model.layers.21.feed_forward.experts.10.w3, model.layers.21.feed_forward.experts.11.w1,
|
| 739 |
+
model.layers.21.feed_forward.experts.11.w3, model.layers.21.feed_forward.experts.12.w1,
|
| 740 |
+
model.layers.21.feed_forward.experts.12.w3, model.layers.21.feed_forward.experts.13.w1,
|
| 741 |
+
model.layers.21.feed_forward.experts.13.w3, model.layers.21.feed_forward.experts.14.w1,
|
| 742 |
+
model.layers.21.feed_forward.experts.14.w3, model.layers.21.feed_forward.experts.15.w1,
|
| 743 |
+
model.layers.21.feed_forward.experts.15.w3, model.layers.21.feed_forward.experts.16.w1,
|
| 744 |
+
model.layers.21.feed_forward.experts.16.w3, model.layers.21.feed_forward.experts.17.w1,
|
| 745 |
+
model.layers.21.feed_forward.experts.17.w3, model.layers.21.feed_forward.experts.18.w1,
|
| 746 |
+
model.layers.21.feed_forward.experts.18.w3, model.layers.21.feed_forward.experts.19.w1,
|
| 747 |
+
model.layers.21.feed_forward.experts.19.w3, model.layers.21.feed_forward.experts.20.w1,
|
| 748 |
+
model.layers.21.feed_forward.experts.20.w3, model.layers.21.feed_forward.experts.21.w1,
|
| 749 |
+
model.layers.21.feed_forward.experts.21.w3, model.layers.21.feed_forward.experts.22.w1,
|
| 750 |
+
model.layers.21.feed_forward.experts.22.w3, model.layers.21.feed_forward.experts.23.w1,
|
| 751 |
+
model.layers.21.feed_forward.experts.23.w3, model.layers.21.feed_forward.experts.24.w1,
|
| 752 |
+
model.layers.21.feed_forward.experts.24.w3, model.layers.21.feed_forward.experts.25.w1,
|
| 753 |
+
model.layers.21.feed_forward.experts.25.w3, model.layers.21.feed_forward.experts.26.w1,
|
| 754 |
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model.layers.21.feed_forward.experts.26.w3, model.layers.21.feed_forward.experts.27.w1,
|
| 755 |
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model.layers.21.feed_forward.experts.27.w3, model.layers.21.feed_forward.experts.28.w1,
|
| 756 |
+
model.layers.21.feed_forward.experts.28.w3, model.layers.21.feed_forward.experts.29.w1,
|
| 757 |
+
model.layers.21.feed_forward.experts.29.w3, model.layers.21.feed_forward.experts.30.w1,
|
| 758 |
+
model.layers.21.feed_forward.experts.30.w3, model.layers.21.feed_forward.experts.31.w1,
|
| 759 |
+
model.layers.21.feed_forward.experts.31.w3]
|
| 760 |
+
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|
| 761 |
+
balance_layers: [model.layers.22.conv.in_proj]
|
| 762 |
+
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|
| 763 |
+
balance_layers: [model.layers.22.feed_forward.gate, model.layers.22.feed_forward.experts.0.w1,
|
| 764 |
+
model.layers.22.feed_forward.experts.0.w3, model.layers.22.feed_forward.experts.1.w1,
|
| 765 |
+
model.layers.22.feed_forward.experts.1.w3, model.layers.22.feed_forward.experts.2.w1,
|
| 766 |
+
model.layers.22.feed_forward.experts.2.w3, model.layers.22.feed_forward.experts.3.w1,
|
| 767 |
+
model.layers.22.feed_forward.experts.3.w3, model.layers.22.feed_forward.experts.4.w1,
|
| 768 |
+
model.layers.22.feed_forward.experts.4.w3, model.layers.22.feed_forward.experts.5.w1,
|
| 769 |
+
model.layers.22.feed_forward.experts.5.w3, model.layers.22.feed_forward.experts.6.w1,
|
| 770 |
+
model.layers.22.feed_forward.experts.6.w3, model.layers.22.feed_forward.experts.7.w1,
|
| 771 |
+
model.layers.22.feed_forward.experts.7.w3, model.layers.22.feed_forward.experts.8.w1,
|
| 772 |
+
model.layers.22.feed_forward.experts.8.w3, model.layers.22.feed_forward.experts.9.w1,
|
| 773 |
+
model.layers.22.feed_forward.experts.9.w3, model.layers.22.feed_forward.experts.10.w1,
|
| 774 |
+
model.layers.22.feed_forward.experts.10.w3, model.layers.22.feed_forward.experts.11.w1,
|
| 775 |
+
model.layers.22.feed_forward.experts.11.w3, model.layers.22.feed_forward.experts.12.w1,
|
| 776 |
+
model.layers.22.feed_forward.experts.12.w3, model.layers.22.feed_forward.experts.13.w1,
|
| 777 |
+
model.layers.22.feed_forward.experts.13.w3, model.layers.22.feed_forward.experts.14.w1,
|
| 778 |
+
model.layers.22.feed_forward.experts.14.w3, model.layers.22.feed_forward.experts.15.w1,
|
| 779 |
+
model.layers.22.feed_forward.experts.15.w3, model.layers.22.feed_forward.experts.16.w1,
|
| 780 |
+
model.layers.22.feed_forward.experts.16.w3, model.layers.22.feed_forward.experts.17.w1,
|
| 781 |
+
model.layers.22.feed_forward.experts.17.w3, model.layers.22.feed_forward.experts.18.w1,
|
| 782 |
+
model.layers.22.feed_forward.experts.18.w3, model.layers.22.feed_forward.experts.19.w1,
|
| 783 |
+
model.layers.22.feed_forward.experts.19.w3, model.layers.22.feed_forward.experts.20.w1,
|
| 784 |
+
model.layers.22.feed_forward.experts.20.w3, model.layers.22.feed_forward.experts.21.w1,
|
| 785 |
+
model.layers.22.feed_forward.experts.21.w3, model.layers.22.feed_forward.experts.22.w1,
|
| 786 |
+
model.layers.22.feed_forward.experts.22.w3, model.layers.22.feed_forward.experts.23.w1,
|
| 787 |
+
model.layers.22.feed_forward.experts.23.w3, model.layers.22.feed_forward.experts.24.w1,
|
| 788 |
+
model.layers.22.feed_forward.experts.24.w3, model.layers.22.feed_forward.experts.25.w1,
|
| 789 |
+
model.layers.22.feed_forward.experts.25.w3, model.layers.22.feed_forward.experts.26.w1,
|
| 790 |
+
model.layers.22.feed_forward.experts.26.w3, model.layers.22.feed_forward.experts.27.w1,
|
| 791 |
+
model.layers.22.feed_forward.experts.27.w3, model.layers.22.feed_forward.experts.28.w1,
|
| 792 |
+
model.layers.22.feed_forward.experts.28.w3, model.layers.22.feed_forward.experts.29.w1,
|
| 793 |
+
model.layers.22.feed_forward.experts.29.w3, model.layers.22.feed_forward.experts.30.w1,
|
| 794 |
+
model.layers.22.feed_forward.experts.30.w3, model.layers.22.feed_forward.experts.31.w1,
|
| 795 |
+
model.layers.22.feed_forward.experts.31.w3]
|
| 796 |
+
- smooth_layer: model.layers.23.operator_norm
|
| 797 |
+
balance_layers: [model.layers.23.conv.in_proj]
|
| 798 |
+
- smooth_layer: model.layers.23.ffn_norm
|
| 799 |
+
balance_layers: [model.layers.23.feed_forward.gate, model.layers.23.feed_forward.experts.0.w1,
|
| 800 |
+
model.layers.23.feed_forward.experts.0.w3, model.layers.23.feed_forward.experts.1.w1,
|
| 801 |
+
model.layers.23.feed_forward.experts.1.w3, model.layers.23.feed_forward.experts.2.w1,
|
| 802 |
+
model.layers.23.feed_forward.experts.2.w3, model.layers.23.feed_forward.experts.3.w1,
|
| 803 |
+
model.layers.23.feed_forward.experts.3.w3, model.layers.23.feed_forward.experts.4.w1,
|
| 804 |
+
model.layers.23.feed_forward.experts.4.w3, model.layers.23.feed_forward.experts.5.w1,
|
| 805 |
+
model.layers.23.feed_forward.experts.5.w3, model.layers.23.feed_forward.experts.6.w1,
|
| 806 |
+
model.layers.23.feed_forward.experts.6.w3, model.layers.23.feed_forward.experts.7.w1,
|
| 807 |
+
model.layers.23.feed_forward.experts.7.w3, model.layers.23.feed_forward.experts.8.w1,
|
| 808 |
+
model.layers.23.feed_forward.experts.8.w3, model.layers.23.feed_forward.experts.9.w1,
|
| 809 |
+
model.layers.23.feed_forward.experts.9.w3, model.layers.23.feed_forward.experts.10.w1,
|
| 810 |
+
model.layers.23.feed_forward.experts.10.w3, model.layers.23.feed_forward.experts.11.w1,
|
| 811 |
+
model.layers.23.feed_forward.experts.11.w3, model.layers.23.feed_forward.experts.12.w1,
|
| 812 |
+
model.layers.23.feed_forward.experts.12.w3, model.layers.23.feed_forward.experts.13.w1,
|
| 813 |
+
model.layers.23.feed_forward.experts.13.w3, model.layers.23.feed_forward.experts.14.w1,
|
| 814 |
+
model.layers.23.feed_forward.experts.14.w3, model.layers.23.feed_forward.experts.15.w1,
|
| 815 |
+
model.layers.23.feed_forward.experts.15.w3, model.layers.23.feed_forward.experts.16.w1,
|
| 816 |
+
model.layers.23.feed_forward.experts.16.w3, model.layers.23.feed_forward.experts.17.w1,
|
| 817 |
+
model.layers.23.feed_forward.experts.17.w3, model.layers.23.feed_forward.experts.18.w1,
|
| 818 |
+
model.layers.23.feed_forward.experts.18.w3, model.layers.23.feed_forward.experts.19.w1,
|
| 819 |
+
model.layers.23.feed_forward.experts.19.w3, model.layers.23.feed_forward.experts.20.w1,
|
| 820 |
+
model.layers.23.feed_forward.experts.20.w3, model.layers.23.feed_forward.experts.21.w1,
|
| 821 |
+
model.layers.23.feed_forward.experts.21.w3, model.layers.23.feed_forward.experts.22.w1,
|
| 822 |
+
model.layers.23.feed_forward.experts.22.w3, model.layers.23.feed_forward.experts.23.w1,
|
| 823 |
+
model.layers.23.feed_forward.experts.23.w3, model.layers.23.feed_forward.experts.24.w1,
|
| 824 |
+
model.layers.23.feed_forward.experts.24.w3, model.layers.23.feed_forward.experts.25.w1,
|
| 825 |
+
model.layers.23.feed_forward.experts.25.w3, model.layers.23.feed_forward.experts.26.w1,
|
| 826 |
+
model.layers.23.feed_forward.experts.26.w3, model.layers.23.feed_forward.experts.27.w1,
|
| 827 |
+
model.layers.23.feed_forward.experts.27.w3, model.layers.23.feed_forward.experts.28.w1,
|
| 828 |
+
model.layers.23.feed_forward.experts.28.w3, model.layers.23.feed_forward.experts.29.w1,
|
| 829 |
+
model.layers.23.feed_forward.experts.29.w3, model.layers.23.feed_forward.experts.30.w1,
|
| 830 |
+
model.layers.23.feed_forward.experts.30.w3, model.layers.23.feed_forward.experts.31.w1,
|
| 831 |
+
model.layers.23.feed_forward.experts.31.w3]
|
| 832 |
+
- smooth_layer: model.embedding_norm
|
| 833 |
+
balance_layers: [lm_head]
|
| 834 |
+
duo_scaling: true
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,23 @@
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|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<|startoftext|>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|im_end|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<|pad|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
}
|
| 23 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
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tokenizer_config.json
ADDED
|
@@ -0,0 +1,4078 @@
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|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": true,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<|pad|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<|startoftext|>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "<|endoftext|>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"3": {
|
| 30 |
+
"content": "<|fim_pre|>",
|
| 31 |
+
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| 3510 |
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