Update README.md

README.md

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 ---
+base_model:
+- ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B
+- vicgalle/Roleplay-Llama-3-8B
+- cgato/L3-TheSpice-8b-v0.1.3
+- ResplendentAI/Kei_Llama3_8B
+library_name: transformers
+tags:
+- mergekit
+- merge
+- 4-bit
+- AWQ
+- text-generation
+- autotrain_compatible
+- endpoints_compatible
+pipeline_tag: text-generation
 inference: false
+quantized_by: Suparious
 ---
 # jeiku/Average_Normie_v2_l3_8B AWQ
 
-** PROCESSING .... ETA 30mins **
-
 - Model creator: [jeiku](https://huggingface.co/jeiku)
 - Original model: [Average_Normie_v2_l3_8B](https://huggingface.co/jeiku/Average_Normie_v2_l3_8B)
 
+## Model Summary
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
+This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [ResplendentAI/Kei_Llama3_8B](https://huggingface.co/ResplendentAI/Kei_Llama3_8B) as a base.
+
+The following models were included in the merge:
+* [ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B](https://huggingface.co/ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B)
+* [vicgalle/Roleplay-Llama-3-8B](https://huggingface.co/vicgalle/Roleplay-Llama-3-8B)
+* [cgato/L3-TheSpice-8b-v0.1.3](https://huggingface.co/cgato/L3-TheSpice-8b-v0.1.3)
+
 ### About AWQ
 
 AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.