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Delta-Vector_Austral-Xgen-9B-Winton-GGUF
tensorblock/Delta-Vector_Austral-Xgen-9B-Winton-GGUF
Delta-Vector_Austral-Xgen-9B-Winton-GGUF is a machine learning model from tensorblock. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
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Repo size
80.9 GB
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Repo makeup
Click a slice to open those files.
.gguf9.3 GB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jul 25, 2025
- Updated
- Jan 27, 2026
- SHA
- 2719d2b9
Base models
Model card
From the Hugging Face model README
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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.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| 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 | Q3_K_S | 4.747 GB | very small, high quality loss |
| 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 | Q3_K_L | 5.671 GB | small, substantial quality loss |
| 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 | Q4_K_S | 6.145 GB | small, greater quality loss |
| 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 | Q5_0 | 7.385 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| 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 | Q5_K_M | 7.569 GB | large, very low quality loss - recommended |
| 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 | Q8_0 | 11.324 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
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:
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'
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Jul 25, 2025
- Updated
- Jan 27, 2026