File size: 7,883 Bytes
60df7b2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
228a5d1
 
 
 
 
 
 
60df7b2
 
 
 
 
 
 
4b53ffd
 
 
a977953
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4b53ffd
 
 
 
 
a977953
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4b53ffd
60df7b2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
---
license: llama3
language:
- tr
- en
base_model: curiositytech/MARS-v0.2
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
model-index:
- name: MARS
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge TR v0.2
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc
      value: 43.85
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag TR
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc
      value: 46.64
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA TR v0.2
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: acc
      value: 48.66
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande TR v0.2
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 52.84
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k TR v0.2
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 59.3
      name: accuracy
---

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>

[![Website](https://img.shields.io/badge/Website-tensorblock.co-blue?logo=google-chrome&logoColor=white)](https://tensorblock.co)
[![Twitter](https://img.shields.io/twitter/follow/tensorblock_aoi?style=social)](https://twitter.com/tensorblock_aoi)
[![Discord](https://img.shields.io/badge/Discord-Join%20Us-5865F2?logo=discord&logoColor=white)](https://discord.gg/Ej5NmeHFf2)
[![GitHub](https://img.shields.io/badge/GitHub-TensorBlock-black?logo=github&logoColor=white)](https://github.com/TensorBlock)
[![Telegram](https://img.shields.io/badge/Telegram-Group-blue?logo=telegram)](https://t.me/TensorBlock)


## curiositytech/MARS-v0.2 - GGUF

This repo contains GGUF format model files for [curiositytech/MARS-v0.2](https://huggingface.co/curiositytech/MARS-v0.2).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

## Our projects
<table border="1" cellspacing="0" cellpadding="10">
  <tr>
    <th colspan="2" style="font-size: 25px;">Forge</th>
  </tr>
  <tr>
    <th colspan="2">
      <img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/>
    </th>
  </tr>
  <tr>
    <th colspan="2">An OpenAI-compatible multi-provider routing layer.</th>
  </tr>
  <tr>
    <th colspan="2">
      <a href="https://github.com/TensorBlock/forge" target="_blank" style="
        display: inline-block;
        padding: 8px 16px;
        background-color: #FF7F50;
        color: white;
        text-decoration: none;
        border-radius: 6px;
        font-weight: bold;
        font-family: sans-serif;
      ">πŸš€ Try it now! πŸš€</a>
    </th>
  </tr>

  <tr>
    <th style="font-size: 25px;">Awesome MCP Servers</th>
    <th style="font-size: 25px;">TensorBlock Studio</th>
  </tr>
  <tr>
    <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th>
    <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th>
  </tr>
  <tr>
    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
    <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
  </tr>
  <tr>
    <th>
      <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
        display: inline-block;
        padding: 8px 16px;
        background-color: #FF7F50;
        color: white;
        text-decoration: none;
        border-radius: 6px;
        font-weight: bold;
        font-family: sans-serif;
      ">πŸ‘€ See what we built πŸ‘€</a>
    </th>
    <th>
      <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
        display: inline-block;
        padding: 8px 16px;
        background-color: #FF7F50;
        color: white;
        text-decoration: none;
        border-radius: 6px;
        font-weight: bold;
        font-family: sans-serif;
      ">πŸ‘€ See what we built πŸ‘€</a>
    </th>
  </tr>
</table>
## Prompt template

```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [MARS-v0.2-Q2_K.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q2_K.gguf) | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes |
| [MARS-v0.2-Q3_K_S.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q3_K_S.gguf) | Q3_K_S | 3.413 GB | very small, high quality loss |
| [MARS-v0.2-Q3_K_M.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q3_K_M.gguf) | Q3_K_M | 3.743 GB | very small, high quality loss |
| [MARS-v0.2-Q3_K_L.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q3_K_L.gguf) | Q3_K_L | 4.025 GB | small, substantial quality loss |
| [MARS-v0.2-Q4_0.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q4_0.gguf) | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [MARS-v0.2-Q4_K_S.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q4_K_S.gguf) | Q4_K_S | 4.370 GB | small, greater quality loss |
| [MARS-v0.2-Q4_K_M.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q4_K_M.gguf) | Q4_K_M | 4.583 GB | medium, balanced quality - recommended |
| [MARS-v0.2-Q5_0.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q5_0.gguf) | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [MARS-v0.2-Q5_K_S.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q5_K_S.gguf) | Q5_K_S | 5.215 GB | large, low quality loss - recommended |
| [MARS-v0.2-Q5_K_M.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q5_K_M.gguf) | Q5_K_M | 5.339 GB | large, very low quality loss - recommended |
| [MARS-v0.2-Q6_K.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q6_K.gguf) | Q6_K | 6.143 GB | very large, extremely low quality loss |
| [MARS-v0.2-Q8_0.gguf](https://huggingface.co/tensorblock/MARS-v0.2-GGUF/blob/main/MARS-v0.2-Q8_0.gguf) | Q8_0 | 7.954 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/MARS-v0.2-GGUF --include "MARS-v0.2-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/MARS-v0.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```