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- Josiefied-Qwen3-8B-abliterated-v1-Q2_K.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q3_K_L.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q3_K_M.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q3_K_S.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q4_0.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q4_K_M.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q4_K_S.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q5_0.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q5_K_M.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q5_K_S.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q6_K.gguf +3 -0
- Josiefied-Qwen3-8B-abliterated-v1-Q8_0.gguf +3 -0
- README.md +150 -0
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README.md
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---
|
2 |
+
tags:
|
3 |
+
- chat
|
4 |
+
- TensorBlock
|
5 |
+
- GGUF
|
6 |
+
base_model: Goekdeniz-Guelmez/Josiefied-Qwen3-8B-abliterated-v1
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pipeline_tag: text-generation
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library_name: transformers
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---
|
10 |
+
|
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<div style="width: auto; margin-left: auto; margin-right: auto">
|
12 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
|
13 |
+
</div>
|
14 |
+
|
15 |
+
[](https://tensorblock.co)
|
16 |
+
[](https://twitter.com/tensorblock_aoi)
|
17 |
+
[](https://discord.gg/Ej5NmeHFf2)
|
18 |
+
[](https://github.com/TensorBlock)
|
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+
[](https://t.me/TensorBlock)
|
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+
|
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+
|
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## Goekdeniz-Guelmez/Josiefied-Qwen3-8B-abliterated-v1 - GGUF
|
23 |
+
|
24 |
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<div style="text-align: left; margin: 20px 0;">
|
25 |
+
<a href="https://discord.com/invite/Ej5NmeHFf2" style="display: inline-block; padding: 10px 20px; background-color: #5865F2; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
|
26 |
+
Join our Discord to learn more about what we're building β
|
27 |
+
</a>
|
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+
</div>
|
29 |
+
|
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+
This repo contains GGUF format model files for [Goekdeniz-Guelmez/Josiefied-Qwen3-8B-abliterated-v1](https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen3-8B-abliterated-v1).
|
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+
|
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).
|
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|
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## Our projects
|
35 |
+
<table border="1" cellspacing="0" cellpadding="10">
|
36 |
+
<tr>
|
37 |
+
<th colspan="2" style="font-size: 25px;">Forge</th>
|
38 |
+
</tr>
|
39 |
+
<tr>
|
40 |
+
<th colspan="2">
|
41 |
+
<img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/>
|
42 |
+
</th>
|
43 |
+
</tr>
|
44 |
+
<tr>
|
45 |
+
<th colspan="2">An OpenAI-compatible multi-provider routing layer.</th>
|
46 |
+
</tr>
|
47 |
+
<tr>
|
48 |
+
<th colspan="2">
|
49 |
+
<a href="https://github.com/TensorBlock/forge" target="_blank" style="
|
50 |
+
display: inline-block;
|
51 |
+
padding: 8px 16px;
|
52 |
+
background-color: #FF7F50;
|
53 |
+
color: white;
|
54 |
+
text-decoration: none;
|
55 |
+
border-radius: 6px;
|
56 |
+
font-weight: bold;
|
57 |
+
font-family: sans-serif;
|
58 |
+
">π Try it now! π</a>
|
59 |
+
</th>
|
60 |
+
</tr>
|
61 |
+
|
62 |
+
<tr>
|
63 |
+
<th style="font-size: 25px;">Awesome MCP Servers</th>
|
64 |
+
<th style="font-size: 25px;">TensorBlock Studio</th>
|
65 |
+
</tr>
|
66 |
+
<tr>
|
67 |
+
<th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th>
|
68 |
+
<th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th>
|
69 |
+
</tr>
|
70 |
+
<tr>
|
71 |
+
<th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
|
72 |
+
<th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
|
73 |
+
</tr>
|
74 |
+
<tr>
|
75 |
+
<th>
|
76 |
+
<a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
|
77 |
+
display: inline-block;
|
78 |
+
padding: 8px 16px;
|
79 |
+
background-color: #FF7F50;
|
80 |
+
color: white;
|
81 |
+
text-decoration: none;
|
82 |
+
border-radius: 6px;
|
83 |
+
font-weight: bold;
|
84 |
+
font-family: sans-serif;
|
85 |
+
">π See what we built π</a>
|
86 |
+
</th>
|
87 |
+
<th>
|
88 |
+
<a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
|
89 |
+
display: inline-block;
|
90 |
+
padding: 8px 16px;
|
91 |
+
background-color: #FF7F50;
|
92 |
+
color: white;
|
93 |
+
text-decoration: none;
|
94 |
+
border-radius: 6px;
|
95 |
+
font-weight: bold;
|
96 |
+
font-family: sans-serif;
|
97 |
+
">π See what we built π</a>
|
98 |
+
</th>
|
99 |
+
</tr>
|
100 |
+
</table>
|
101 |
+
|
102 |
+
## Prompt template
|
103 |
+
|
104 |
+
```
|
105 |
+
<|im_start|>system
|
106 |
+
{system_prompt}<|im_end|>
|
107 |
+
<|im_start|>user
|
108 |
+
{prompt}<|im_end|>
|
109 |
+
<|im_start|>assistant
|
110 |
+
```
|
111 |
+
|
112 |
+
## Model file specification
|
113 |
+
|
114 |
+
| Filename | Quant type | File Size | Description |
|
115 |
+
| -------- | ---------- | --------- | ----------- |
|
116 |
+
| [Josiefied-Qwen3-8B-abliterated-v1-Q2_K.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q2_K.gguf) | Q2_K | 3.282 GB | smallest, significant quality loss - not recommended for most purposes |
|
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+
| [Josiefied-Qwen3-8B-abliterated-v1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q3_K_S.gguf) | Q3_K_S | 3.770 GB | very small, high quality loss |
|
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| [Josiefied-Qwen3-8B-abliterated-v1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q3_K_M.gguf) | Q3_K_M | 4.124 GB | very small, high quality loss |
|
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| [Josiefied-Qwen3-8B-abliterated-v1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q3_K_L.gguf) | Q3_K_L | 4.431 GB | small, substantial quality loss |
|
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+
| [Josiefied-Qwen3-8B-abliterated-v1-Q4_0.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q4_0.gguf) | Q4_0 | 4.775 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
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| [Josiefied-Qwen3-8B-abliterated-v1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q4_K_S.gguf) | Q4_K_S | 4.802 GB | small, greater quality loss |
|
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| [Josiefied-Qwen3-8B-abliterated-v1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q4_K_M.gguf) | Q4_K_M | 5.028 GB | medium, balanced quality - recommended |
|
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| [Josiefied-Qwen3-8B-abliterated-v1-Q5_0.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q5_0.gguf) | Q5_0 | 5.721 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
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| [Josiefied-Qwen3-8B-abliterated-v1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q5_K_S.gguf) | Q5_K_S | 5.721 GB | large, low quality loss - recommended |
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125 |
+
| [Josiefied-Qwen3-8B-abliterated-v1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q5_K_M.gguf) | Q5_K_M | 5.851 GB | large, very low quality loss - recommended |
|
126 |
+
| [Josiefied-Qwen3-8B-abliterated-v1-Q6_K.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q6_K.gguf) | Q6_K | 6.726 GB | very large, extremely low quality loss |
|
127 |
+
| [Josiefied-Qwen3-8B-abliterated-v1-Q8_0.gguf](https://huggingface.co/tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF/blob/main/Josiefied-Qwen3-8B-abliterated-v1-Q8_0.gguf) | Q8_0 | 8.710 GB | very large, extremely low quality loss - not recommended |
|
128 |
+
|
129 |
+
|
130 |
+
## Downloading instruction
|
131 |
+
|
132 |
+
### Command line
|
133 |
+
|
134 |
+
Firstly, install Huggingface Client
|
135 |
+
|
136 |
+
```shell
|
137 |
+
pip install -U "huggingface_hub[cli]"
|
138 |
+
```
|
139 |
+
|
140 |
+
Then, downoad the individual model file the a local directory
|
141 |
+
|
142 |
+
```shell
|
143 |
+
huggingface-cli download tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF --include "Josiefied-Qwen3-8B-abliterated-v1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
144 |
+
```
|
145 |
+
|
146 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
147 |
+
|
148 |
+
```shell
|
149 |
+
huggingface-cli download tensorblock/Goekdeniz-Guelmez_Josiefied-Qwen3-8B-abliterated-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
150 |
+
```
|