Update README.md

README.md

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 This model was converted to GGUF format from [`Hastagaras/Zabuza-8B-Llama-3.1`](https://huggingface.co/Hastagaras/Zabuza-8B-Llama-3.1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/Hastagaras/Zabuza-8B-Llama-3.1) for more details on the model.
 
+---
+Model details:
+-
+This model is a combination of merge, abliteration technique (using baukit) and finetuning.
+
+The base model is arcee-ai/Llama-3.1-SuperNova-Lite, which underwent abliteration to reduce model refusals.
+
+Next, I finetuned the abliterated SuperNova-Lite with 10K diverse examples such as:
+
+    Claude and Gemini Instruction/RP (15k sloppy examples were removed!, but some may have slipped through.)
+    Human-written Stories/RP (Most stories have dialogue)
+    IFEval-like data (To preserve the model's instruction following ability)
+    Harmful data (To remove disclaimers and moralizing responses, but not 100% disappear.)
+    My sarcastic and rude AI assistant data (Just for my personal satisfaction)
+
+Lastly, I merged the model using TIES, inspired by this MERGE by Joseph717171.
+
+Chat Template
+-
+Llama 3.1 Instruct
+-
+<|start_header_id|>{role}<|end_header_id|>
+
+{message}<|eot_id|><|start_header_id|>{role}<|end_header_id|>
+
+{message}<|eot_id|>
+
+System messages for role-playing should be very detailed if you don't want dry responses.
+
+Configuration
+-
+This is a merge of pre-trained language models created using mergekit.
+
+The following YAML configuration was used to produce this model:
+
+models:
+  - model: Hastagaras/snovalite-baukit-6-14.FT-L5-7.13-22.27-31
+    parameters:
+      weight: 1
+      density: 1
+
+  - model: Hastagaras/snovalite-baukit-6-14.FT-L5-7.13-22.27-31
+    parameters:
+      weight: 1
+      density: 1
+
+merge_method: ties
+base_model: meta-llama/Llama-3.1-8B
+parameters:
+  density: 1
+  normalize: true
+  int8_mask: true
+dtype: bfloat16
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)