---
base_model:
- mistralai/Mistral-7B-v0.1
- cognitivecomputations/dolphin-2.2.1-mistral-7b
- HuggingFaceH4/zephyr-7b-beta
- NousResearch/Hermes-2-Pro-Mistral-7B
library_name: transformers
tags:
- mergekit
- merge
widget:
- text: "Is this review positive or negative? Review: Best cast iron skillet you will ever buy."
  example_title: "Sentiment analysis"
- text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday. He chose her because she had ..."
  example_title: "Coreference resolution"
- text: "On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book ..."
  example_title: "Logic puzzles"
- text: "The two men running to become New York City's next mayor will face off in their first debate Wednesday night ..."
  example_title: "Reading comprehension"
---
# Herdolphyr

This is a quantitized merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) as a base.

### Models Merged

The following models were included in the merge:
* [cognitivecomputations/dolphin-2.2.1-mistral-7b](https://huggingface.co/cognitivecomputations/dolphin-2.2.1-mistral-7b)
* [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)
* [NousResearch/Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: cognitivecomputations/dolphin-2.2.1-mistral-7b
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: HuggingFaceH4/zephyr-7b-beta 
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: NousResearch/Hermes-2-Pro-Mistral-7B
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1 
parameters:
  normalize: true
  int8_mask: true
dtype: float16
```