Update README.md

README.md

@@ -1,3 +1,75 @@
 ---
 license: cc-by-nc-4.0
+tags:
+- GGUF
+- iMat
+- llama3
 ---
+
+```
+  e88 88e                               d8     
+ d888 888b  8888 8888  ,"Y88b 888 8e   d88     
+C8888 8888D 8888 8888 "8" 888 888 88b d88888   
+ Y888 888P  Y888 888P ,ee 888 888 888  888     
+  "88 88"    "88 88"  "88 888 888 888  888     
+      b                                        
+      8b,                                      
+ 
+  e88'Y88                  d8           888    
+ d888  'Y  ,"Y88b 888,8,  d88    ,e e,  888    
+C8888     "8" 888 888 "  d88888 d88 88b 888    
+ Y888  ,d ,ee 888 888     888   888   , 888    
+  "88,d88 "88 888 888     888    "YeeP" 888    
+                                               
+PROUDLY PRESENTS         
+```
+
+## Llama-3-8B-EGO-iMat-GGUF
+
+
+Quantized from fp32 with love.
+* Weighted quantizations were calculated using groups_merged.txt with 105 chunks (recommended amount for this file) and n_ctx=512. Special thanks to jukofyork for sharing [this process](https://huggingface.co/jukofyork/WizardLM-2-8x22B-imatrix)
+
+<b>**Note - Please use SillyTavern as well as the following prompt format:**</b>
+```
+[EGO]Name: Character name and then Everything that forms the personality and speech patterns.(i.e. scenario, sample dialogue, character definitions, etc)[/EGO]
+[SEEN]User message.[/SEEN]
+Character Name:
+```
+
+
+For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747)
+
+<b>All quants are verified working prior to uploading to repo for your safety and convenience. </b>
+
+Please note importance matrix quantizations are a work in progress. IQ4 and above is recommended for best results.
+
+Original model card [here](https://huggingface.co/Envoid/Llama-3-8B-EGO) and below
+
+---
+
+# This model isn't particularly great. It's just an undercooked experiment.
+
+Releasing it anyways just in case it accidentally makes good merge meat. 
+
+# It also has a tendency to produce mature content without warning. 
+
+This model is tuned off of the base Llama-3-8B model. 
+
+I adapted the leaked Undi dataset into training samples for custom formatting. This model pretty much only functions properly in SillyTavern. 
+
+The formatting has two pairs of pseudotokens
+
+```
+[EGO]Name: Character name and then Everything that forms the personality and speech patterns.(i.e. scenario, sample dialogue, character definitions, etc)[/EGO]
+[SEEN]User message.[/SEEN]
+Character Name:
+```
+
+The self attention modules were fine tuned separately on this dataset and the pseudotokens were chosen because they made logical sense with respect to the character giving a reply without allowing the model to 'connect the dots' during training and figure out that it is indeed an AI language model.
+
+After this was done all modules were then finetuned together on the dendrite dataset in order to connect the changes made to the attention modules.
+
+So with regards to building a SillyTavern prompt template you basically want the entire story string and any additional stylistic instructions enclosed in the [EGO] tags and then the user messages enclosed in [SEEN] tags. 
+
+It doesn't give particularly verbose replies unless you're continueing a roleplay with verbose messages. Otherwise it's pretty bad.