---
license: apache-2.0
tags:
- MoE
- merge
- mergekit
- Mistral
- Microsoft/WizardLM-2-7B
---

# WizardLM-2-4x7B-MoE

The model is currently uploading and should be available in a couple of hours!

This is an experimental MoE model made with [Mergekit](https://github.com/arcee-ai/mergekit). It was made by combining four [WizardLM-2-7B](https://huggingface.co/microsoft/WizardLM-2-7B) models using the random gate mode. Please be sure to set experts per token to 4 for the best results! Context length should be the same as Mistral-7B-Instruct-v0.1 (8k tokens). For instruction templates, Vicuna-v1.1 is recommended.

# Quanitized versions

Hopefully coming soon.

# Evaluation

I don't expect this model to be that great since it's something that I made as an experiment. However, I will submit it to the Open LLM Leaderboard to see how it matches up against some other models (particularly WizardLM-2-7B and WizardLM-2-70B). 

# Mergekit config
```
base_model: models/WizardLM-2-7B
gate_mode: random
dtype: float16
experts_per_token: 4
experts:
  - source_model: models/WizardLM-2-7B
  - source_model: models/WizardLM-2-7B
  - source_model: models/WizardLM-2-7B
  - source_model: models/WizardLM-2-7B
```