---
license: other
tags:
- llama2
---
# Model Card: ZaraXLS L2 7b
This model uses [Nous Hermes Llama2 7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) (53%) as a base with [Stable Beluga 7b](https://huggingface.co/stabilityai/StableBeluga-7B) (47%) and the result of this merge was merged with [Airoboros LMOE Creative 7b 2.1](https://huggingface.co/jondurbin/airoboros-lmoe-7b-2.1) and [LimaRP LLama2 7B Lora version of the day 07/23/2023](https://huggingface.co/lemonilia/limarp-llama2).

This merge of models(hermes and stable beluga) was done with this [script](https://github.com/zarakiquemparte/zaraki-tools/blob/main/merge-cli.py)

This merge of Lora with Model was done with this [script](https://github.com/zarakiquemparte/zaraki-tools/blob/main/apply-lora.py)

Merge illustration:

![illustration](zaraxls-merge-illustration.png)

## Usage:

Since this is a merge between Nous Hermes, Stable Beluga and LimaRP, the following instruction formats should work:

Alpaca 2:

```
### Instruction:
<prompt>

### Response:
<leave a newline blank for model to respond>
```

LimaRP instruction format:

```
<<SYSTEM>>
<character card and system prompt>

<<USER>>
<prompt>

<<AIBOT>>
<leave a newline blank for model to respond>
```

## Bias, Risks, and Limitations

This model is not intended for supplying factual information or advice in any form

## Training Details

This model is merged and can be reproduced using the tools mentioned above. Please refer to all provided links for extra model-specific details.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_zarakiquemparte__zaraxls-l2-7b)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 47.89   |
| ARC (25-shot)         | 54.44          |
| HellaSwag (10-shot)   | 78.94    |
| MMLU (5-shot)         | 50.39         |
| TruthfulQA (0-shot)   | 46.51   |
| Winogrande (5-shot)   | 73.16   |
| GSM8K (5-shot)        | 0.23        |
| DROP (3-shot)         | 31.59         |