Hugging Face's logo

tensorblock
/
distilabeled-Marcoro14-7B-slerp-full-GGUF

GGUF
English
distilabel
dpo
rlaif
rlhf
Merge
mergekit
TensorBlock
GGUF
Eval Results (legacy)
Model card Files
xet
 Community
distilabeled-Marcoro14-7B-slerp-full-GGUF
File size: 10,195 Bytes
1f07c8b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4e86551
 
 
 
 
 
 
1f07c8b
 
 
 
 
 
 
507f0f7
 
 
f1a07c5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
507f0f7
 
 
 
 
f1a07c5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
507f0f7
1f07c8b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
---
language:
- en
license: apache-2.0
tags:
- distilabel
- dpo
- rlaif
- rlhf
- merge
- mergekit
- TensorBlock
- GGUF
datasets:
- argilla/distilabel-intel-orca-dpo-pairs
base_model: argilla/distilabeled-Marcoro14-7B-slerp-full
model-index:
- name: distilabeled-Marcoro14-7B-slerp-full
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 70.65
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/distilabeled-Marcoro14-7B-slerp-full
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 87.55
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/distilabeled-Marcoro14-7B-slerp-full
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 65.33
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/distilabeled-Marcoro14-7B-slerp-full
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 64.21
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/distilabeled-Marcoro14-7B-slerp-full
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 82.0
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/distilabeled-Marcoro14-7B-slerp-full
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 70.66
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=argilla/distilabeled-Marcoro14-7B-slerp-full
      name: Open LLM Leaderboard
---

<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)


## argilla/distilabeled-Marcoro14-7B-slerp-full - GGUF

This repo contains GGUF format model files for [argilla/distilabeled-Marcoro14-7B-slerp-full](https://huggingface.co/argilla/distilabeled-Marcoro14-7B-slerp-full).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](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;
      ">🚀 Try it now! 🚀</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;
      ">👀 See what we built 👀</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;
      ">👀 See what we built 👀</a>
    </th>
  </tr>
</table>
## Prompt template

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [distilabeled-Marcoro14-7B-slerp-full-Q2_K.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q2_K.gguf) | Q2_K | 2.719 GB | smallest, significant quality loss - not recommended for most purposes |
| [distilabeled-Marcoro14-7B-slerp-full-Q3_K_S.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q3_K_S.gguf) | Q3_K_S | 3.165 GB | very small, high quality loss |
| [distilabeled-Marcoro14-7B-slerp-full-Q3_K_M.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q3_K_M.gguf) | Q3_K_M | 3.519 GB | very small, high quality loss |
| [distilabeled-Marcoro14-7B-slerp-full-Q3_K_L.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q3_K_L.gguf) | Q3_K_L | 3.822 GB | small, substantial quality loss |
| [distilabeled-Marcoro14-7B-slerp-full-Q4_0.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q4_0.gguf) | Q4_0 | 4.109 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [distilabeled-Marcoro14-7B-slerp-full-Q4_K_S.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q4_K_S.gguf) | Q4_K_S | 4.140 GB | small, greater quality loss |
| [distilabeled-Marcoro14-7B-slerp-full-Q4_K_M.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q4_K_M.gguf) | Q4_K_M | 4.368 GB | medium, balanced quality - recommended |
| [distilabeled-Marcoro14-7B-slerp-full-Q5_0.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q5_0.gguf) | Q5_0 | 4.998 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [distilabeled-Marcoro14-7B-slerp-full-Q5_K_S.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q5_K_S.gguf) | Q5_K_S | 4.998 GB | large, low quality loss - recommended |
| [distilabeled-Marcoro14-7B-slerp-full-Q5_K_M.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q5_K_M.gguf) | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
| [distilabeled-Marcoro14-7B-slerp-full-Q6_K.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q6_K.gguf) | Q6_K | 5.942 GB | very large, extremely low quality loss |
| [distilabeled-Marcoro14-7B-slerp-full-Q8_0.gguf](https://huggingface.co/tensorblock/distilabeled-Marcoro14-7B-slerp-full-GGUF/blob/main/distilabeled-Marcoro14-7B-slerp-full-Q8_0.gguf) | Q8_0 | 7.696 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/distilabeled-Marcoro14-7B-slerp-full-GGUF --include "distilabeled-Marcoro14-7B-slerp-full-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/distilabeled-Marcoro14-7B-slerp-full-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```