GGUF
English
TensorBlock
GGUF
conversational
File size: 6,913 Bytes
2d15fbd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c5ac4f3
 
 
 
 
 
 
2d15fbd
 
 
 
 
 
 
840aa84
0756d4c
 
 
bfbc334
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0756d4c
 
 
 
 
bfbc334
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0756d4c
2d15fbd
 
840aa84
2d15fbd
 
 
 
 
 
 
 
840aa84
 
 
 
 
 
 
 
 
 
 
 
2d15fbd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
datasets:
- SenseLLM/ReflectionSeq-GPT
- SenseLLM/ReflectionSeq-DS
language:
- en
base_model: SenseLLM/ReflectionCoder-DS-33B
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>

[![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)


## SenseLLM/ReflectionCoder-DS-33B - GGUF

This repo contains GGUF format model files for [SenseLLM/ReflectionCoder-DS-33B](https://huggingface.co/SenseLLM/ReflectionCoder-DS-33B).

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;
      ">🚀 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


```
<|system|><|text|>{system_prompt}<|endofblock|><|endofmessage|><|user|><|text|>{prompt}<|endofblock|><|endofmessage|><|assistant|>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [ReflectionCoder-DS-33B-Q2_K.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q2_K.gguf) | Q2_K | 11.505 GB | smallest, significant quality loss - not recommended for most purposes |
| [ReflectionCoder-DS-33B-Q3_K_S.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q3_K_S.gguf) | Q3_K_S | 13.429 GB | very small, high quality loss |
| [ReflectionCoder-DS-33B-Q3_K_M.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q3_K_M.gguf) | Q3_K_M | 14.985 GB | very small, high quality loss |
| [ReflectionCoder-DS-33B-Q3_K_L.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q3_K_L.gguf) | Q3_K_L | 16.352 GB | small, substantial quality loss |
| [ReflectionCoder-DS-33B-Q4_0.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q4_0.gguf) | Q4_0 | 17.525 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [ReflectionCoder-DS-33B-Q4_K_S.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q4_K_S.gguf) | Q4_K_S | 17.640 GB | small, greater quality loss |
| [ReflectionCoder-DS-33B-Q4_K_M.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q4_K_M.gguf) | Q4_K_M | 18.569 GB | medium, balanced quality - recommended |
| [ReflectionCoder-DS-33B-Q5_0.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q5_0.gguf) | Q5_0 | 21.379 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [ReflectionCoder-DS-33B-Q5_K_S.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q5_K_S.gguf) | Q5_K_S | 21.379 GB | large, low quality loss - recommended |
| [ReflectionCoder-DS-33B-Q5_K_M.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q5_K_M.gguf) | Q5_K_M | 21.917 GB | large, very low quality loss - recommended |
| [ReflectionCoder-DS-33B-Q6_K.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q6_K.gguf) | Q6_K | 25.475 GB | very large, extremely low quality loss |
| [ReflectionCoder-DS-33B-Q8_0.gguf](https://huggingface.co/tensorblock/ReflectionCoder-DS-33B-GGUF/blob/main/ReflectionCoder-DS-33B-Q8_0.gguf) | Q8_0 | 32.994 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/ReflectionCoder-DS-33B-GGUF --include "ReflectionCoder-DS-33B-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/ReflectionCoder-DS-33B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```