Create README.md

README.md

@@ -0,0 +1,52 @@
+---
+license: cc-by-nc-4.0
+tags:
+- not-for-all-audiences
+---
+```
+  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         
+```
+# L3.1-8B-Llamoutcast-exl2-longcal
+
+Quantized using 115 rows of 8192 tokens from the default ExLlamav2-calibration dataset.
+
+Branches:
+- `main` -- `measurement.json`
+- `8b8h` -- 8bpw, 8bit lm_head
+- `6b8h` -- 6bpw, 8bit lm_head
+- `4b6h` -- 4bpw, 6bit lm_head
+- `2.25b6h` -- 2.25bpw, 6bit lm_head
+
+Original model link: [Envoid/L3.1-8B-Llamoutcast](https://huggingface.co/Envoid/L3.1-8B-Llamoutcast)
+
+### Quanter's notes
+As apparently the default dataset is supposed to be better in nearly all situations, I decided to start quanting using that in addition to my standard rpcal-fare. I'd appreciate real-world tests to confirm the hypothesis, though, so please leave a comment if you find this mode of quanting better than rpcal.
+
+Original model README below.
+
+-----
+![](https://files.catbox.moe/ecgn0m.jpg)
+
+# Warning: this model is utterly cursed.
+
+## Llamoutcast
+
+This model was originally intended to be a DADA finetune of Llama-3.1-8B-Instruct but the results were unsatisfactory. So it received some additional finetuning on a rawtext dataset and now it is utterly cursed. 
+
+It responds to Llama-3 Instruct formatting.
+
+Trained using [qlora-pipe](https://github.com/tdrussell/qlora-pipe).