File size: 6,893 Bytes
ce35565 b6656b0 ce35565 4602d89 e0e7154 4602d89 e0e7154 4602d89 ce35565 |
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 |
---
datasets:
- PowerInfer/QWQ-LONGCOT-500K
- PowerInfer/LONGCOT-Refine-500K
base_model: PowerInfer/SmallThinker-3B-Preview
tags:
- TensorBlock
- GGUF
---
<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>
[](https://tensorblock.co)
[](https://twitter.com/tensorblock_aoi)
[](https://discord.gg/Ej5NmeHFf2)
[](https://github.com/TensorBlock)
[](https://t.me/TensorBlock)
## PowerInfer/SmallThinker-3B-Preview - GGUF
This repo contains GGUF format model files for [PowerInfer/SmallThinker-3B-Preview](https://huggingface.co/PowerInfer/SmallThinker-3B-Preview).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4391](https://github.com/ggerganov/llama.cpp/commit/9ba399dfa7f115effc63d48e6860a94c9faa31b2).
## 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;
">π Try it now! π</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;
">π See what we built π</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;
">π See what we built π</a>
</th>
</tr>
</table>
## Prompt template
```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [SmallThinker-3B-Preview-Q2_K.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q2_K.gguf) | Q2_K | 1.377 GB | smallest, significant quality loss - not recommended for most purposes |
| [SmallThinker-3B-Preview-Q3_K_S.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q3_K_S.gguf) | Q3_K_S | 1.588 GB | very small, high quality loss |
| [SmallThinker-3B-Preview-Q3_K_M.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q3_K_M.gguf) | Q3_K_M | 1.724 GB | very small, high quality loss |
| [SmallThinker-3B-Preview-Q3_K_L.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q3_K_L.gguf) | Q3_K_L | 1.841 GB | small, substantial quality loss |
| [SmallThinker-3B-Preview-Q4_0.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q4_0.gguf) | Q4_0 | 1.998 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [SmallThinker-3B-Preview-Q4_K_S.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q4_K_S.gguf) | Q4_K_S | 2.009 GB | small, greater quality loss |
| [SmallThinker-3B-Preview-Q4_K_M.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q4_K_M.gguf) | Q4_K_M | 2.105 GB | medium, balanced quality - recommended |
| [SmallThinker-3B-Preview-Q5_0.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q5_0.gguf) | Q5_0 | 2.384 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [SmallThinker-3B-Preview-Q5_K_S.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q5_K_S.gguf) | Q5_K_S | 2.384 GB | large, low quality loss - recommended |
| [SmallThinker-3B-Preview-Q5_K_M.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q5_K_M.gguf) | Q5_K_M | 2.439 GB | large, very low quality loss - recommended |
| [SmallThinker-3B-Preview-Q6_K.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q6_K.gguf) | Q6_K | 2.793 GB | very large, extremely low quality loss |
| [SmallThinker-3B-Preview-Q8_0.gguf](https://huggingface.co/tensorblock/SmallThinker-3B-Preview-GGUF/blob/main/SmallThinker-3B-Preview-Q8_0.gguf) | Q8_0 | 3.616 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/SmallThinker-3B-Preview-GGUF --include "SmallThinker-3B-Preview-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/SmallThinker-3B-Preview-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|