Hugging Face's logo

tensorblock
/
phi-2-super-GGUF

Text Generation
GGUF
English
convAI
conversational
TensorBlock
GGUF
Eval Results (legacy)
Model card Files
xet
Community
phi-2-super-GGUF
File size: 6,973 Bytes 
289eeaf
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
84dd135
 
 
 
 
 
 
289eeaf
 
 
 
 
 
 
e9b03ee
 
 
06bacdd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e9b03ee
 
 
 
 
06bacdd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e9b03ee
289eeaf
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
---
license: mit
license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE
language:
- en
widget:
- text: Hello who are you?
  example_title: Identity
- text: What can you do?
  example_title: Capabilities
- text: Create a fastapi endpoint to retrieve the weather given a zip code.
  example_title: Coding
tags:
- convAI
- conversational
- TensorBlock
- GGUF
pipeline_tag: text-generation
base_model: abacaj/phi-2-super
model-index:
- name: phi-2-super
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Instruction Following Eval
      type: wis-k/instruction-following-eval
    metrics:
    - type: acc
      value: 0.2717
      name: prompt_level_loose_acc
    source:
      url: https://github.com/huggingface/lighteval
      name: LightEval
---

<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)


## abacaj/phi-2-super - GGUF

This repo contains GGUF format model files for [abacaj/phi-2-super](https://huggingface.co/abacaj/phi-2-super).

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

```
<|endoftext|>[INST] {prompt} [/INST]
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [phi-2-super-Q2_K.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q2_K.gguf) | Q2_K | 1.110 GB | smallest, significant quality loss - not recommended for most purposes |
| [phi-2-super-Q3_K_S.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q3_K_S.gguf) | Q3_K_S | 1.251 GB | very small, high quality loss |
| [phi-2-super-Q3_K_M.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q3_K_M.gguf) | Q3_K_M | 1.426 GB | very small, high quality loss |
| [phi-2-super-Q3_K_L.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q3_K_L.gguf) | Q3_K_L | 1.575 GB | small, substantial quality loss |
| [phi-2-super-Q4_0.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q4_0.gguf) | Q4_0 | 1.602 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [phi-2-super-Q4_K_S.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q4_K_S.gguf) | Q4_K_S | 1.619 GB | small, greater quality loss |
| [phi-2-super-Q4_K_M.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q4_K_M.gguf) | Q4_K_M | 1.738 GB | medium, balanced quality - recommended |
| [phi-2-super-Q5_0.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q5_0.gguf) | Q5_0 | 1.933 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [phi-2-super-Q5_K_S.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q5_K_S.gguf) | Q5_K_S | 1.933 GB | large, low quality loss - recommended |
| [phi-2-super-Q5_K_M.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q5_K_M.gguf) | Q5_K_M | 2.003 GB | large, very low quality loss - recommended |
| [phi-2-super-Q6_K.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q6_K.gguf) | Q6_K | 2.285 GB | very large, extremely low quality loss |
| [phi-2-super-Q8_0.gguf](https://huggingface.co/tensorblock/phi-2-super-GGUF/blob/main/phi-2-super-Q8_0.gguf) | Q8_0 | 2.958 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/phi-2-super-GGUF --include "phi-2-super-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/phi-2-super-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```