File size: 6,541 Bytes
fa6d9b5
 
 
 
 
 
 
 
 
 
 
06aec4c
 
 
 
 
 
 
fa6d9b5
 
 
 
 
 
 
 
 
 
33b8841
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fa6d9b5
 
 
 
 
33b8841
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fa6d9b5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
tags:
- TensorBlock
- GGUF
base_model: nickypro/tinyllama-42M
---

<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)


## nickypro/tinyllama-42M - GGUF

This repo contains GGUF format model files for [nickypro/tinyllama-42M](https://huggingface.co/nickypro/tinyllama-42M).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5165](https://github.com/ggml-org/llama.cpp/commit/1d735c0b4fa0551c51c2f4ac888dd9a01f447985).

## 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

```
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [tinyllama-42M-Q2_K.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q2_K.gguf) | Q2_K | 0.030 GB | smallest, significant quality loss - not recommended for most purposes |
| [tinyllama-42M-Q3_K_S.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q3_K_S.gguf) | Q3_K_S | 0.033 GB | very small, high quality loss |
| [tinyllama-42M-Q3_K_M.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q3_K_M.gguf) | Q3_K_M | 0.034 GB | very small, high quality loss |
| [tinyllama-42M-Q3_K_L.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q3_K_L.gguf) | Q3_K_L | 0.035 GB | small, substantial quality loss |
| [tinyllama-42M-Q4_0.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q4_0.gguf) | Q4_0 | 0.038 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [tinyllama-42M-Q4_K_S.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q4_K_S.gguf) | Q4_K_S | 0.039 GB | small, greater quality loss |
| [tinyllama-42M-Q4_K_M.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q4_K_M.gguf) | Q4_K_M | 0.040 GB | medium, balanced quality - recommended |
| [tinyllama-42M-Q5_0.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q5_0.gguf) | Q5_0 | 0.043 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [tinyllama-42M-Q5_K_S.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q5_K_S.gguf) | Q5_K_S | 0.043 GB | large, low quality loss - recommended |
| [tinyllama-42M-Q5_K_M.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q5_K_M.gguf) | Q5_K_M | 0.044 GB | large, very low quality loss - recommended |
| [tinyllama-42M-Q6_K.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q6_K.gguf) | Q6_K | 0.050 GB | very large, extremely low quality loss |
| [tinyllama-42M-Q8_0.gguf](https://huggingface.co/tensorblock/nickypro_tinyllama-42M-GGUF/blob/main/tinyllama-42M-Q8_0.gguf) | Q8_0 | 0.062 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/nickypro_tinyllama-42M-GGUF --include "tinyllama-42M-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/nickypro_tinyllama-42M-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```