初始化项目，由ModelHub XC社区提供模型

Model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
Source: Original Platform

README.md

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+---
+license: cc-by-nc-4.0
+language:
+- en
+tags:
+- merge
+base_model:
+- janai-hq/trinity-v1
+- EmbeddedLLM/Mistral-7B-Merge-14-v0
+---
+
+# Update 2023-12-19
+
+In light of [dataset contamination issue among the merged models](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/474)
+raised by the community in recent days, in particular
+[berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha),
+[Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling), and
+[janai-hq/trinity-v1](https://huggingface.co/janai-hq/trinity-v1),
+we decided to remake another model without the models mentioned.
+Additionally, their CC-by-NC-4.0 license is restrictive and thus are not suitable for an open model.
+
+# Open LLM Leaderboard
+For reference, this model obtained an average score of 72.88.
+
+| Average    | 72.88 |
+|------------|-------|
+| ARC        | 68.86 |
+| HellaSwag  | 87.01 |
+| MMLU       | 65.05 |
+| TruthfulQA | 64.19 |
+| Winogrande | 81.69 |
+| GSM8K      | 70.51  |
+
+
+# Model Description
+This is an experiment to test merging 14 models using DARE TIES 🦙
+
+The merged model is then merged again with [janai-hq/trinity-v1](https://huggingface.co/janai-hq/trinity-v1) using Gradient SLERP.
+The result is a base model that performs quite well but requires some further instruction fine-tuning.
+
+The 14 models are as follows:
+1. [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
+2. [ehartford/dolphin-2.2.1-mistral-7b](https://huggingface.co/ehartford/dolphin-2.2.1-mistral-7b)
+3. [SciPhi/SciPhi-Mistral-7B-32k](https://huggingface.co/SciPhi/SciPhi-Mistral-7B-32k)
+4. [ehartford/samantha-1.2-mistral-7b](https://huggingface.co/ehartford/samantha-1.2-mistral-7b)
+5. [Arc53/docsgpt-7b-mistral](https://huggingface.co/Arc53/docsgpt-7b-mistral)
+6. [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
+7. [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling)
+8. [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
+9. [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B)
+10. [beowolx/MistralHermes-CodePro-7B-v1](https://huggingface.co/beowolx/MistralHermes-CodePro-7B-v1)
+11. [TIGER-Lab/MAmmoTH-7B-Mistral](https://huggingface.co/TIGER-Lab/MAmmoTH-7B-Mistral)
+12. [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
+13. [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp)
+14. [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
+
+- base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+
+The yaml config file for this model is here:
+
+```yaml
+slices:
+  - sources:
+      - model: janai-hq/trinity-v1
+        layer_range: [0, 32]
+      - model: EmbeddedLLM/Mistral-7B-Merge-14-v0
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: janai-hq/trinity-v1
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16
+
+```