Update README.md

README.md

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 ---
 license: apache-2.0
+tags:
+- merge
+- moe
 ---
+Open_Gpt4_v0.2
+
+This is the quantized gguf version for inference. If you want the unquantized version please reffer to the repo bellow:
+
+- https://huggingface.co/rombodawg/Open_Gpt4_8x7B_v0.2
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/T7QKB0fKNHQvNqAjm8zrH.jpeg)
+
+This model is a TIES merger of Mixtral-8x7B-Instruct-v0.1  and bagel-dpo-8x7b-v0.2 with MixtralOrochi8x7B being the Base model.
+
+
+I was very impressed with MixtralOrochi8x7B performance and multifaceted usecases as it is already a merger of many usefull Mixtral models such as Mixtral instruct, 
+Noromaid-v0.1-mixtral, openbuddy-mixtral and possibly other models that were not named. My goal was to expand the models capabilities and make it even more useful of a model, maybe even competitive with closed source models like Gpt-4. But for that more testing is required. I hope the community can help me determine if its deserving of its name. 😊
+
+This is the second iteration of this model, using better models in the merger to improve performance (hopefully).
+
+Base model: 
+
+- https://huggingface.co/smelborp/MixtralOrochi8x7B
+
+Merged models:
+
+- https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
+
+- https://huggingface.co/jondurbin/bagel-dpo-8x7b-v0.2
+
+
+Instruct template: Alpaca
+
+
+Merger config:
+```
+models:
+  - model: Mixtral-8x7B-Instruct-v0.1
+    parameters:
+      density: .5
+      weight: 1
+  - model: bagel-dpo-8x7b-v0.2
+    parameters:
+      density: .5
+      weight: .7
+
+
+merge_method: ties
+base_model: MixtralOrochi8x7B
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: float16
+
+```