
# Model Description
This is an experiment to compare merging 2 models using DARE TIES versus SLERP 🦙

We are mainly interested to compare against [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp)

The 2 models involved in the merge as follows:
1. [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
2. [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3)

- base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)

The yaml config file for the merge is:

```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: teknium/OpenHermes-2.5-Mistral-7B
    parameters:
      weight: 0.5
      density: 0.5
  - model: Intel/neural-chat-7b-v3-3
    parameters:
      weight: 0.5
      density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16
```

# Open LLM Leaderboard

Note that with more tuning DARE TIES might achieve better results.

|            | DARE TIES | SLERP |
|------------|-----------|-------|
| Average    | 70.69     | 71.38 |
| ARC        | 67.49     | 68.09 |
| HellaSwag  | 85.78     | 86.2  |
| MMLU       | 64.1      | 64.26 |
| TruthfulQA | 60.52     | 62.78 |
| Winogrande | 79.01     | 79.16 |
| GSM8K      | 67.25     | 67.78 |


{"language": ["en"], "license": "apache-2.0", "tags": ["merge"], "base_model": ["teknium/OpenHermes-2.5-Mistral-7B", "Intel/neural-chat-7b-v3-3"]}
transformers safetensors mistral text-generation merge en base_model:teknium/OpenHermes-2.5-Mistral-7B base_model:Intel/neural-chat-7b-v3-3 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us