初始化项目，由ModelHub XC社区提供模型

Model: EmbeddedLLM/Mistral-7B-Merge-02-v0
Source: Original Platform

README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- merge
+base_model:
+- teknium/OpenHermes-2.5-Mistral-7B
+- Intel/neural-chat-7b-v3-3
+---
+
+# 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 |
+