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Model: EmbeddedLLM/Mistral-7B-Merge-14-v0.4
Source: Original Platform

README.md

@@ -0,0 +1,60 @@
+---
+license: apache-2.0
+language:
+- en
+tags:
+- merge
+base_model:
+- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
+- EmbeddedLLM/Mistral-7B-Merge-14-v0.3
+---
+
+# Model Description
+This is an experiment to test merging 14 models using DARE TIES 🦙
+
+We first merge 14 models to produce [EmbeddedLLM/Mistral-7B-Merge-14-v0.3](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.3),
+which is then merged again with [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp) using Gradient SLERP.
+The result is a model that performs quite well but may require further instruction fine-tuning.
+
+## Open LLM Leaderboard
+
+| Average    | 71.19 |
+|------------|-------|
+| ARC        | 66.81 |
+| HellaSwag  | 86.15 |
+| MMLU       | 65.10 |
+| TruthfulQA | 58.25 |
+| Winogrande | 80.03 |
+| GSM8K      | 70.81  |
+
+## Chat Template
+
+Either ChatML or Llama-2 chat template.
+
+## Merge Configuration
+
+The merge config file for this model is here:
+
+```yaml
+slices:
+  - sources:
+      - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
+        layer_range: [0, 32]
+      - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.3
+        layer_range: [0, 32]
+
+merge_method: slerp
+base_model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-openchat-3.5-1210-Slerp
+
+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 # fallback for rest of tensors
+tokenizer_source: base
+embed_slerp: true
+
+dtype: bfloat16
+```