---
license: apache-2.0
language:
- en
base_model: prithivMLmods/Sombrero-QwQ-32B-Elite11
pipeline_tag: text-generation
library_name: transformers
tags:
- StreamlinedMemory
- text-generation-inference
- TensorBlock
- GGUF
---
[](https://tensorblock.co)
[](https://twitter.com/tensorblock_aoi)
[](https://discord.gg/Ej5NmeHFf2)
[](https://github.com/TensorBlock)
[](https://t.me/TensorBlock)
## prithivMLmods/Sombrero-QwQ-32B-Elite11 - GGUF
This repo contains GGUF format model files for [prithivMLmods/Sombrero-QwQ-32B-Elite11](https://huggingface.co/prithivMLmods/Sombrero-QwQ-32B-Elite11).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4882](https://github.com/ggml-org/llama.cpp/commit/be7c3034108473beda214fd1d7c98fd6a7a3bdf5).
## Our projects
## 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 |
| -------- | ---------- | --------- | ----------- |
| [Sombrero-QwQ-32B-Elite11-Q2_K.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q2_K.gguf) | Q2_K | 12.313 GB | smallest, significant quality loss - not recommended for most purposes |
| [Sombrero-QwQ-32B-Elite11-Q3_K_S.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q3_K_S.gguf) | Q3_K_S | 14.392 GB | very small, high quality loss |
| [Sombrero-QwQ-32B-Elite11-Q3_K_M.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q3_K_M.gguf) | Q3_K_M | 15.935 GB | very small, high quality loss |
| [Sombrero-QwQ-32B-Elite11-Q3_K_L.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q3_K_L.gguf) | Q3_K_L | 17.247 GB | small, substantial quality loss |
| [Sombrero-QwQ-32B-Elite11-Q4_0.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q4_0.gguf) | Q4_0 | 18.640 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Sombrero-QwQ-32B-Elite11-Q4_K_S.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q4_K_S.gguf) | Q4_K_S | 18.784 GB | small, greater quality loss |
| [Sombrero-QwQ-32B-Elite11-Q4_K_M.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q4_K_M.gguf) | Q4_K_M | 19.851 GB | medium, balanced quality - recommended |
| [Sombrero-QwQ-32B-Elite11-Q5_0.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q5_0.gguf) | Q5_0 | 22.638 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Sombrero-QwQ-32B-Elite11-Q5_K_S.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q5_K_S.gguf) | Q5_K_S | 22.638 GB | large, low quality loss - recommended |
| [Sombrero-QwQ-32B-Elite11-Q5_K_M.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q5_K_M.gguf) | Q5_K_M | 23.262 GB | large, very low quality loss - recommended |
| [Sombrero-QwQ-32B-Elite11-Q6_K.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q6_K.gguf) | Q6_K | 26.886 GB | very large, extremely low quality loss |
| [Sombrero-QwQ-32B-Elite11-Q8_0.gguf](https://huggingface.co/tensorblock/Sombrero-QwQ-32B-Elite11-GGUF/blob/main/Sombrero-QwQ-32B-Elite11-Q8_0.gguf) | Q8_0 | 34.821 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/Sombrero-QwQ-32B-Elite11-GGUF --include "Sombrero-QwQ-32B-Elite11-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/Sombrero-QwQ-32B-Elite11-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```