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---
license: apache-2.0
base_model: albertfares/DPO_MCQA_model_3_06_04_08
tags:
- merge
- sft
- dpo
- qwen3
- math
- code
- mcqa
- mnlp-m3
- TensorBlock
- GGUF
datasets:
- albertfares/MNLP_M3_dpo_dataset
language:
- en
pipeline_tag: text-generation
---

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## albertfares/DPO_MCQA_model_3_06_04_08 - GGUF

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        Join our Discord to learn more about what we're building ↗
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This repo contains GGUF format model files for [albertfares/DPO_MCQA_model_3_06_04_08](https://huggingface.co/albertfares/DPO_MCQA_model_3_06_04_08).

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).

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## 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 |
| -------- | ---------- | --------- | ----------- |
| [DPO_MCQA_model_3_06_04_08-Q2_K.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q2_K.gguf) | Q2_K | 0.347 GB | smallest, significant quality loss - not recommended for most purposes |
| [DPO_MCQA_model_3_06_04_08-Q3_K_S.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q3_K_S.gguf) | Q3_K_S | 0.390 GB | very small, high quality loss |
| [DPO_MCQA_model_3_06_04_08-Q3_K_M.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q3_K_M.gguf) | Q3_K_M | 0.414 GB | very small, high quality loss |
| [DPO_MCQA_model_3_06_04_08-Q3_K_L.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q3_K_L.gguf) | Q3_K_L | 0.435 GB | small, substantial quality loss |
| [DPO_MCQA_model_3_06_04_08-Q4_0.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q4_0.gguf) | Q4_0 | 0.469 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [DPO_MCQA_model_3_06_04_08-Q4_K_S.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q4_K_S.gguf) | Q4_K_S | 0.471 GB | small, greater quality loss |
| [DPO_MCQA_model_3_06_04_08-Q4_K_M.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q4_K_M.gguf) | Q4_K_M | 0.484 GB | medium, balanced quality - recommended |
| [DPO_MCQA_model_3_06_04_08-Q5_0.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q5_0.gguf) | Q5_0 | 0.544 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [DPO_MCQA_model_3_06_04_08-Q5_K_S.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q5_K_S.gguf) | Q5_K_S | 0.544 GB | large, low quality loss - recommended |
| [DPO_MCQA_model_3_06_04_08-Q5_K_M.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q5_K_M.gguf) | Q5_K_M | 0.551 GB | large, very low quality loss - recommended |
| [DPO_MCQA_model_3_06_04_08-Q6_K.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q6_K.gguf) | Q6_K | 0.623 GB | very large, extremely low quality loss |
| [DPO_MCQA_model_3_06_04_08-Q8_0.gguf](https://huggingface.co/tensorblock/albertfares_DPO_MCQA_model_3_06_04_08-GGUF/blob/main/DPO_MCQA_model_3_06_04_08-Q8_0.gguf) | Q8_0 | 0.805 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/albertfares_DPO_MCQA_model_3_06_04_08-GGUF --include "DPO_MCQA_model_3_06_04_08-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/albertfares_DPO_MCQA_model_3_06_04_08-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```