---
base_model: kuotient/EEVE-Math-10.8B
license: cc-by-sa-4.0
language:
- ko
tags:
- math
- TensorBlock
- GGUF
datasets:
- kuotient/orca-math-word-problems-193k-korean
model-index:
- name: EEVE-Math-10.8B
  results:
  - task:
      type: text-generation
    dataset:
      name: gsm8k-ko
      type: gsm8k
    metrics:
    - type: pass@1
      value: 0.539
      name: pass@1
      verified: false
---

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## kuotient/EEVE-Math-10.8B - GGUF

This repo contains GGUF format model files for [kuotient/EEVE-Math-10.8B](https://huggingface.co/kuotient/EEVE-Math-10.8B).

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).

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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 |
| -------- | ---------- | --------- | ----------- |
| [EEVE-Math-10.8B-Q2_K.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q2_K.gguf) | Q2_K | 4.046 GB | smallest, significant quality loss - not recommended for most purposes |
| [EEVE-Math-10.8B-Q3_K_S.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q3_K_S.gguf) | Q3_K_S | 4.711 GB | very small, high quality loss |
| [EEVE-Math-10.8B-Q3_K_M.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q3_K_M.gguf) | Q3_K_M | 5.242 GB | very small, high quality loss |
| [EEVE-Math-10.8B-Q3_K_L.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q3_K_L.gguf) | Q3_K_L | 5.697 GB | small, substantial quality loss |
| [EEVE-Math-10.8B-Q4_0.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q4_0.gguf) | Q4_0 | 6.123 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [EEVE-Math-10.8B-Q4_K_S.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q4_K_S.gguf) | Q4_K_S | 6.169 GB | small, greater quality loss |
| [EEVE-Math-10.8B-Q4_K_M.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q4_K_M.gguf) | Q4_K_M | 6.513 GB | medium, balanced quality - recommended |
| [EEVE-Math-10.8B-Q5_0.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q5_0.gguf) | Q5_0 | 7.453 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [EEVE-Math-10.8B-Q5_K_S.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q5_K_S.gguf) | Q5_K_S | 7.453 GB | large, low quality loss - recommended |
| [EEVE-Math-10.8B-Q5_K_M.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q5_K_M.gguf) | Q5_K_M | 7.653 GB | large, very low quality loss - recommended |
| [EEVE-Math-10.8B-Q6_K.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q6_K.gguf) | Q6_K | 8.866 GB | very large, extremely low quality loss |
| [EEVE-Math-10.8B-Q8_0.gguf](https://huggingface.co/tensorblock/EEVE-Math-10.8B-GGUF/blob/main/EEVE-Math-10.8B-Q8_0.gguf) | Q8_0 | 11.482 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/EEVE-Math-10.8B-GGUF --include "EEVE-Math-10.8B-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/EEVE-Math-10.8B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```