transformers safetensors mistral text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us
### exl2 quant (measurement.json included)
---
### original readme below
---
---
license: cc-by-nc-4.0
language:
- en
tags:
- merge
base_model:
- EmbeddedLLM/Mistral-7B-Merge-14-v0.3
- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
- openchat/openchat-3.5-0106
- mlabonne/NeuralMarcoro14-7B
---

# Update 2024-01-21

Due to [mlabonne/NeuralMarcoro14-7B](https://huggingface.co/mlabonne/NeuralMarcoro14-7B) updating its license to CC-BY-NC, our license will follow suit.

# Model Description

This is an experiment to test merging 14 models using DARE TIES 🦙

1. We first merge 14 models to produce [EmbeddedLLM/Mistral-7B-Merge-14-v0.3](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.3).
2. The model is merged again using DARE TIES with:
   - [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp)
   - [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106)
   - [mlabonne/NeuralMarcoro14-7B](https://huggingface.co/mlabonne/NeuralMarcoro14-7B)

## Open LLM Leaderboard

| Average    | 71.96 |
|------------|-------|
| ARC        | 68.69 |
| HellaSwag  | 86.45 |
| MMLU       | 65.65 |
| TruthfulQA | 59.12 |
| Winogrande | 80.66 |
| GSM8K      | 71.19  |

## Chat Template

Either ChatML or Llama-2 chat template.

## Merge Configuration

The merge config file for this model is here:

```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.3
    parameters:
      weight: 0.3
      density: 0.5
  - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
    parameters:
      weight: 0.2
      density: 0.5
  - model: openchat/openchat-3.5-0106
    parameters:
      weight: 0.2
      density: 0.5
  - model: mlabonne/NeuralMarcoro14-7B
    parameters:
      weight: 0.3
      density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1

parameters:
  int8_mask: true
tokenizer_source: union
dtype: bfloat16
```
