README.md

---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- ifable/gemma-2-Ifable-9B
- jsgreenawalt/gemma-2-9B-it-advanced-v2.1
model-index:
- name: Gemma-2-Ataraxy-v2-9B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 21.36
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 39.8
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 0.83
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 12.3
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 4.88
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 35.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B
      name: Open LLM Leaderboard
quantized_by: bartowski
pipeline_tag: text-generation
---

## Exllama v2 Quantizations of Gemma-2-Ataraxy-v2-9B

Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.2.2">turboderp's ExLlamaV2 v0.2.2</a> for quantization.

<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>

Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.

Original model: https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2-9B

## Prompt format

```
<bos>{system_prompt}<start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model
<end_of_turn>

```

## Available sizes

| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
| [8_0](https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-exl2/tree/8_0) | 8.0 | 8.0 | 11.9 GB | 15.9 GB | 21.3 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-exl2/tree/6_5) | 6.5 | 8.0 | 10.4 GB | 14.4 GB | 19.8 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
| [5_0](https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-exl2/tree/5_0) | 5.0 | 6.0 | 8.6 GB | 12.6 GB | 18.0 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
| [4_25](https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-exl2/tree/4_25) | 4.25 | 6.0 | 7.9 GB | 11.9 GB | 17.3 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| [3_5](https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-exl2/tree/3_5) | 3.5 | 6.0 | 7.1 GB | 11.1 GB | 16.9 GB | Lower quality, only use if you have to. |

## Download instructions

With git:

```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-exl2 Gemma-2-Ataraxy-v2-9B-exl2-6_5
```

With huggingface hub (credit to TheBloke for instructions):

```shell
pip3 install huggingface-hub
```

To download a specific branch, use the `--revision` parameter. For example, to download the 6.5 bpw branch:

Linux:

```shell
huggingface-cli download bartowski/Gemma-2-Ataraxy-v2-9B-exl2 --revision 6_5 --local-dir Gemma-2-Ataraxy-v2-9B-exl2-6_5
```

Windows (which apparently doesn't like _ in folders sometimes?):

```shell
huggingface-cli download bartowski/Gemma-2-Ataraxy-v2-9B-exl2 --revision 6_5 --local-dir Gemma-2-Ataraxy-v2-9B-exl2-6.5
```

Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski