Update README.md

README.md

@@ -1,3 +1,77 @@
 ---
 license: apache-2.0
 ---
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/x44nNbPTpv0zGTqA1Jb2q.png)
+
+---
+**NOTE**
+Model and Model card from: https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
+This repo is mainly to share quantized gguf to use with clients like LMStudio, contains q4 and q8 quantization along with f16.
+
+How to quantize?
+https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#prepare-data--run
+---
+
+# OpenHermes-2.5-neural-chat-v3-3-Slerp
+
+This is the model for OpenHermes-2.5-neural-chat-v3-3-Slerp. I used [mergekit](https://github.com/cg123/mergekit) to merge models.
+
+# Prompt Templates
+
+You can use these prompt templates, but I recommend using ChatML.
+
+### ChatML [(OpenHermes-2.5-Mistral-7B)](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B):
+
+```
+<|im_start|>system
+{system}<|im_end|>
+<|im_start|>user
+{user}<|im_end|>
+<|im_start|>assistant
+{asistant}<|im_end|>
+```
+
+### [neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3):
+
+```
+### System:
+{system}
+### User:
+{user}
+### Assistant:
+```
+
+# Yaml Config to reproduce
+
+```yaml
+slices:
+  - sources:
+      - model: teknium/OpenHermes-2.5-Mistral-7B
+        layer_range: [0, 32]
+      - model: Intel/neural-chat-7b-v3-3
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: mistralai/Mistral-7B-v0.1
+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
+dtype: bfloat16
+```
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__OpenHermes-2.5-neural-chat-v3-3-Slerp)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 71.38   |
+| ARC (25-shot)         | 68.09          |
+| HellaSwag (10-shot)   | 86.2    |
+| MMLU (5-shot)         | 64.26         |
+| TruthfulQA (0-shot)   | 62.78  |
+| Winogrande (5-shot)   | 79.16  |
+| GSM8K (5-shot)        | 67.78        |