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---
license: apache-2.0
base_model: Delta-Vector/Austral-Xgen-9B-Winton
language:
- en
library_name: transformers
tags:
- roleplay
- finetune
- axolotl
- adventure
- creative-writing
- Llama
- 9B
- 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>
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## Delta-Vector/Austral-Xgen-9B-Winton - GGUF
<div style="text-align: left; margin: 20px 0;">
 <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;">
 Join our Discord to learn more about what we're building ↗
 </a>
</div>
This repo contains GGUF format model files for [Delta-Vector/Austral-Xgen-9B-Winton](https://huggingface.co/Delta-Vector/Austral-Xgen-9B-Winton).
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).
## 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
```
<|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 |
| -------- | ---------- | --------- | ----------- |
| [Austral-Xgen-9B-Winton-Q2_K.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q2_K.gguf) | Q2_K | 4.097 GB | smallest, significant quality loss - not recommended for most purposes |
| [Austral-Xgen-9B-Winton-Q3_K_S.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q3_K_S.gguf) | Q3_K_S | 4.747 GB | very small, high quality loss |
| [Austral-Xgen-9B-Winton-Q3_K_M.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q3_K_M.gguf) | Q3_K_M | 5.239 GB | very small, high quality loss |
| [Austral-Xgen-9B-Winton-Q3_K_L.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q3_K_L.gguf) | Q3_K_L | 5.671 GB | small, substantial quality loss |
| [Austral-Xgen-9B-Winton-Q4_0.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q4_0.gguf) | Q4_0 | 6.106 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Austral-Xgen-9B-Winton-Q4_K_S.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q4_K_S.gguf) | Q4_K_S | 6.145 GB | small, greater quality loss |
| [Austral-Xgen-9B-Winton-Q4_K_M.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q4_K_M.gguf) | Q4_K_M | 6.463 GB | medium, balanced quality - recommended |
| [Austral-Xgen-9B-Winton-Q5_0.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q5_0.gguf) | Q5_0 | 7.385 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Austral-Xgen-9B-Winton-Q5_K_S.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q5_K_S.gguf) | Q5_K_S | 7.385 GB | large, low quality loss - recommended |
| [Austral-Xgen-9B-Winton-Q5_K_M.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q5_K_M.gguf) | Q5_K_M | 7.569 GB | large, very low quality loss - recommended |
| [Austral-Xgen-9B-Winton-Q6_K.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q6_K.gguf) | Q6_K | 8.744 GB | very large, extremely low quality loss |
| [Austral-Xgen-9B-Winton-Q8_0.gguf](https://huggingface.co/tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF/blob/main/Austral-Xgen-9B-Winton-Q8_0.gguf) | Q8_0 | 11.324 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/Delta-Vector_Austral-Xgen-9B-Winton-GGUF --include "Austral-Xgen-9B-Winton-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/Delta-Vector_Austral-Xgen-9B-Winton-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```