File size: 6,662 Bytes
fbb6bfb
 
 
 
 
 
 
 
 
 
 
0fb012b
 
 
 
0cd1273
 
 
 
 
 
 
0fb012b
 
 
 
 
 
 
fbb6bfb
 
 
7b8e525
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fbb6bfb
 
 
 
 
7b8e525
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fbb6bfb
0fb012b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: other
library_name: transformers
license_name: deepseek
license_link: https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
base_model: semcoder/semcoder_1030
---

<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)


## semcoder/semcoder_1030 - GGUF

This repo contains GGUF format model files for [semcoder/semcoder_1030](https://huggingface.co/semcoder/semcoder_1030).

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

```
<|begin▁of▁sentence|>You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable <Code> according to <NL_Description>

<NL_Description>
{prompt}

<Code>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [semcoder_1030-Q2_K.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q2_K.gguf) | Q2_K | 2.535 GB | smallest, significant quality loss - not recommended for most purposes |
| [semcoder_1030-Q3_K_S.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q3_K_S.gguf) | Q3_K_S | 2.950 GB | very small, high quality loss |
| [semcoder_1030-Q3_K_M.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q3_K_M.gguf) | Q3_K_M | 3.300 GB | very small, high quality loss |
| [semcoder_1030-Q3_K_L.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q3_K_L.gguf) | Q3_K_L | 3.599 GB | small, substantial quality loss |
| [semcoder_1030-Q4_0.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q4_0.gguf) | Q4_0 | 3.828 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [semcoder_1030-Q4_K_S.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q4_K_S.gguf) | Q4_K_S | 3.859 GB | small, greater quality loss |
| [semcoder_1030-Q4_K_M.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q4_K_M.gguf) | Q4_K_M | 4.083 GB | medium, balanced quality - recommended |
| [semcoder_1030-Q5_0.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [semcoder_1030-Q5_K_S.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended |
| [semcoder_1030-Q5_K_M.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q5_K_M.gguf) | Q5_K_M | 4.785 GB | large, very low quality loss - recommended |
| [semcoder_1030-Q6_K.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q6_K.gguf) | Q6_K | 5.531 GB | very large, extremely low quality loss |
| [semcoder_1030-Q8_0.gguf](https://huggingface.co/tensorblock/semcoder_1030-GGUF/blob/main/semcoder_1030-Q8_0.gguf) | Q8_0 | 7.164 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/semcoder_1030-GGUF --include "semcoder_1030-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/semcoder_1030-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```