---
license: gemma
library_name: transformers
pipeline_tag: text-generation
base_model: AALF/gemma-2-27b-it-SimPO-37K
tags:
- alignment-handbook
- generated_from_trainer
- TensorBlock
- GGUF
---
## AALF/gemma-2-27b-it-SimPO-37K - GGUF
This repo contains GGUF format model files for [AALF/gemma-2-27b-it-SimPO-37K](https://huggingface.co/AALF/gemma-2-27b-it-SimPO-37K).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
## Prompt template
```
user
{system_prompt}
{prompt}
model
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [gemma-2-27b-it-SimPO-37K-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q2_K.gguf) | Q2_K | 9.732 GB | smallest, significant quality loss - not recommended for most purposes |
| [gemma-2-27b-it-SimPO-37K-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q3_K_S.gguf) | Q3_K_S | 11.333 GB | very small, high quality loss |
| [gemma-2-27b-it-SimPO-37K-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q3_K_M.gguf) | Q3_K_M | 12.503 GB | very small, high quality loss |
| [gemma-2-27b-it-SimPO-37K-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q3_K_L.gguf) | Q3_K_L | 13.522 GB | small, substantial quality loss |
| [gemma-2-27b-it-SimPO-37K-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q4_0.gguf) | Q4_0 | 14.555 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [gemma-2-27b-it-SimPO-37K-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q4_K_S.gguf) | Q4_K_S | 14.658 GB | small, greater quality loss |
| [gemma-2-27b-it-SimPO-37K-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q4_K_M.gguf) | Q4_K_M | 15.502 GB | medium, balanced quality - recommended |
| [gemma-2-27b-it-SimPO-37K-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q5_0.gguf) | Q5_0 | 17.587 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [gemma-2-27b-it-SimPO-37K-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q5_K_S.gguf) | Q5_K_S | 17.587 GB | large, low quality loss - recommended |
| [gemma-2-27b-it-SimPO-37K-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q5_K_M.gguf) | Q5_K_M | 18.075 GB | large, very low quality loss - recommended |
| [gemma-2-27b-it-SimPO-37K-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q6_K.gguf) | Q6_K | 20.809 GB | very large, extremely low quality loss |
| [gemma-2-27b-it-SimPO-37K-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-2-27b-it-SimPO-37K-GGUF/tree/main/gemma-2-27b-it-SimPO-37K-Q8_0.gguf) | Q8_0 | 26.950 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/gemma-2-27b-it-SimPO-37K-GGUF --include "gemma-2-27b-it-SimPO-37K-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/gemma-2-27b-it-SimPO-37K-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```