GGUF
English
TensorBlock
GGUF
conversational
File size: 6,913 Bytes
e8af509
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bb41234
 
 
 
 
 
 
e8af509
 
 
 
 
 
 
0f0fc8e
162d69c
 
 
dff8021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
162d69c
 
 
 
 
dff8021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
162d69c
e8af509
 
0f0fc8e
e8af509
 
 
 
 
 
 
 
0f0fc8e
 
 
 
 
 
 
 
 
 
 
 
e8af509
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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-CL-34B
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-CL-34B - GGUF

This repo contains GGUF format model files for [SenseLLM/ReflectionCoder-CL-34B](https://huggingface.co/SenseLLM/ReflectionCoder-CL-34B).

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;
      ">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


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

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [ReflectionCoder-CL-34B-Q2_K.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q2_K.gguf) | Q2_K | 11.647 GB | smallest, significant quality loss - not recommended for most purposes |
| [ReflectionCoder-CL-34B-Q3_K_S.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q3_K_S.gguf) | Q3_K_S | 13.602 GB | very small, high quality loss |
| [ReflectionCoder-CL-34B-Q3_K_M.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q3_K_M.gguf) | Q3_K_M | 15.186 GB | very small, high quality loss |
| [ReflectionCoder-CL-34B-Q3_K_L.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q3_K_L.gguf) | Q3_K_L | 16.551 GB | small, substantial quality loss |
| [ReflectionCoder-CL-34B-Q4_0.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q4_0.gguf) | Q4_0 | 17.744 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [ReflectionCoder-CL-34B-Q4_K_S.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q4_K_S.gguf) | Q4_K_S | 17.874 GB | small, greater quality loss |
| [ReflectionCoder-CL-34B-Q4_K_M.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q4_K_M.gguf) | Q4_K_M | 18.831 GB | medium, balanced quality - recommended |
| [ReflectionCoder-CL-34B-Q5_0.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q5_0.gguf) | Q5_0 | 21.641 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [ReflectionCoder-CL-34B-Q5_K_S.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q5_K_S.gguf) | Q5_K_S | 21.641 GB | large, low quality loss - recommended |
| [ReflectionCoder-CL-34B-Q5_K_M.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q5_K_M.gguf) | Q5_K_M | 22.202 GB | large, very low quality loss - recommended |
| [ReflectionCoder-CL-34B-Q6_K.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q6_K.gguf) | Q6_K | 25.783 GB | very large, extremely low quality loss |
| [ReflectionCoder-CL-34B-Q8_0.gguf](https://huggingface.co/tensorblock/ReflectionCoder-CL-34B-GGUF/blob/main/ReflectionCoder-CL-34B-Q8_0.gguf) | Q8_0 | 33.394 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-CL-34B-GGUF --include "ReflectionCoder-CL-34B-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-CL-34B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```