File size: 3,474 Bytes
fbd72f9
 
 
 
 
 
 
 
 
 
 
 
9b3b517
 
fbd72f9
 
 
 
 
 
9b3b517
fbd72f9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
63cbf77
 
 
358b46e
 
 
 
 
 
 
 
63cbf77
3bc5e69
 
684e229
3bc5e69
 
 
 
 
358b46e
8890add
2893784
8890add
2893784
8890add
2893784
 
 
 
8890add
 
 
fbd72f9
 
 
8890add
fbd72f9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
---
license: apache-2.0
language:
- en
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>

<p align="center">
    <a
 href="https://jan.ai/">Jan</a> 
    - <a href="https://discord.gg/AsJ8krTT3N">Discord</a>
</p>
<!-- header end -->

# Model Description
This model uses the `SLERP` method to merge [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) with 2 best models in 12th Dec on [OpenLLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard):
1. [Marcoroni-7B-v3](https://huggingface.co/AIDC-ai-business/Marcoroni-7B-v3)
2. [go-bruins-v2](https://huggingface.co/rwitz/go-bruins-v2)

- base model: [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)

The yaml config file for this model is here:

```yaml
slices:
  - sources:
      - model: AIDC-ai-business/Marcoroni-7B-v3
        layer_range: [0, 32]
      - model: rwitz/go-bruins-v2
        layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-Instruct-v0.2
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 
dtype: bfloat16
```

# Prompt template:

- **ChatML**

```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
- **Alpaca**
```
{system_message}

### Instruction:
{prompt}

### Response:
```

# Run this model
You can run this model using [Jan Desktop](https://jan.ai/) on Mac, Windows, or Linux.

Jan is an open source, ChatGPT alternative that is:

- ๐Ÿ’ป  **100% offline on your machine**: Your conversations remain confidential, and visible only to you.
- ๐Ÿ—‚๏ธ **An Open File Format**: Conversations and model settings stay on your computer and can be exported or deleted at any time.
- ๐ŸŒ **OpenAI Compatible**: Local server on port `1337` with OpenAI compatible endpoints
- ๐ŸŒ **Open Source & Free**: We build in public; check out our [Github](https://github.com/janhq)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/r7VmEBLGXpPLTu2MImM7S.png)

# About Jan
Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.


Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.

# Jan Model Merger
This is a test project for merging models.

# Open LLM Leaderboard Evaluation Results

Detailed results can be found here.

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | ?|
| ARC (25-shot)         | ?          |
| HellaSwag (10-shot)   | ?   |
| MMLU (5-shot)         | ?|
| TruthfulQA (0-shot)   | ? |
| Winogrande (5-shot)   | ?  |
| GSM8K (5-shot)        | ?        |

# Acknowlegement
- [mergekit](https://github.com/cg123/mergekit)
- [DARE](https://github.com/yule-BUAA/MergeLM/blob/main/README.md)
- [SLERP](https://github.com/Digitous/LLM-SLERP-Merge)
- [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)