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MN-12B-Mag-Mell-R1-GGUF

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MN-12B-Mag-Mell-R1-GGUF
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---
base_model: inflatebot/MN-12B-Mag-Mell-R1
library_name: transformers
tags:
- mergekit
- merge
- 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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## inflatebot/MN-12B-Mag-Mell-R1 - GGUF

This repo contains GGUF format model files for [inflatebot/MN-12B-Mag-Mell-R1](https://huggingface.co/inflatebot/MN-12B-Mag-Mell-R1).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

## Our projects
<table border="1" cellspacing="0" cellpadding="10">
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        display: inline-block;
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      ">🚀 Try it now! 🚀</a>
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      ">👀 See what we built 👀</a>
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        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 |
| -------- | ---------- | --------- | ----------- |
| [MN-12B-Mag-Mell-R1-Q2_K.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q2_K.gguf) | Q2_K | 4.791 GB | smallest, significant quality loss - not recommended for most purposes |
| [MN-12B-Mag-Mell-R1-Q3_K_S.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q3_K_S.gguf) | Q3_K_S | 5.534 GB | very small, high quality loss |
| [MN-12B-Mag-Mell-R1-Q3_K_M.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q3_K_M.gguf) | Q3_K_M | 6.083 GB | very small, high quality loss |
| [MN-12B-Mag-Mell-R1-Q3_K_L.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q3_K_L.gguf) | Q3_K_L | 6.562 GB | small, substantial quality loss |
| [MN-12B-Mag-Mell-R1-Q4_0.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q4_0.gguf) | Q4_0 | 7.072 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [MN-12B-Mag-Mell-R1-Q4_K_S.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q4_K_S.gguf) | Q4_K_S | 7.120 GB | small, greater quality loss |
| [MN-12B-Mag-Mell-R1-Q4_K_M.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q4_K_M.gguf) | Q4_K_M | 7.477 GB | medium, balanced quality - recommended |
| [MN-12B-Mag-Mell-R1-Q5_0.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q5_0.gguf) | Q5_0 | 8.519 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [MN-12B-Mag-Mell-R1-Q5_K_S.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q5_K_S.gguf) | Q5_K_S | 8.519 GB | large, low quality loss - recommended |
| [MN-12B-Mag-Mell-R1-Q5_K_M.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q5_K_M.gguf) | Q5_K_M | 8.728 GB | large, very low quality loss - recommended |
| [MN-12B-Mag-Mell-R1-Q6_K.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q6_K.gguf) | Q6_K | 10.056 GB | very large, extremely low quality loss |
| [MN-12B-Mag-Mell-R1-Q8_0.gguf](https://huggingface.co/tensorblock/MN-12B-Mag-Mell-R1-GGUF/blob/main/MN-12B-Mag-Mell-R1-Q8_0.gguf) | Q8_0 | 13.022 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/MN-12B-Mag-Mell-R1-GGUF --include "MN-12B-Mag-Mell-R1-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/MN-12B-Mag-Mell-R1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```