Update README.md

README.md

@@ -4,56 +4,20 @@ language:
 - en
 pipeline_tag: conversational
 ---
-# Goliath 120B
+Another EXL2 version of AlpinDale's https://huggingface.co/alpindale/goliath-120b this one being at 2.64BPW.
 
-An auto-regressive causal LM created by combining 2x finetuned [Llama-2 70B](https://huggingface.co/meta-llama/llama-2-70b-hf) into one.
+[2.37BPW](https://huggingface.co/LavaPlanet/Goliath120B-exl2-2.37bpw)
 
-Please check out the quantized formats provided by [@TheBloke](https:///huggingface.co/TheBloke) and [@Panchovix](https://huggingface.co/Panchovix):
+Pippa llama2 Chat was used as the calibration dataset.
 
-- [GGUF](https://huggingface.co/TheBloke/goliath-120b-GGUF) (llama.cpp)
-- [GPTQ](https://huggingface.co/TheBloke/goliath-120b-GPTQ) (KoboldAI, TGW, Aphrodite)
-- [AWQ](https://huggingface.co/TheBloke/goliath-120b-AWQ) (TGW, Aphrodite, vLLM)
-- [Exllamav2](https://huggingface.co/Panchovix/goliath-120b-exl2) (TGW, KoboldAI)
-
-# Prompting Format
-
-Both Vicuna and Alpaca will work, but due the initial and final layers belonging primarily to Xwin, I expect Vicuna to work the best.
-
-# Merge process
-
-The models used in the merge are [Xwin](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1) and [Euryale](https://huggingface.co/Sao10K/Euryale-1.3-L2-70B).
-
-The layer ranges used are as follows:
+Can be run on two RTX 3090s w/ 24GB vram each.
 
+Assuming Windows overhead, the following figures should be more or less close enough for estimation of your own use. 
 ```yaml
-- range 0, 16
-  Xwin
-- range 8, 24
-  Euryale
-- range 17, 32
-  Xwin
-- range 25, 40
-  Euryale
-- range 33, 48
-  Xwin
-- range 41, 56
-  Euryale
-- range 49, 64
-  Xwin
-- range 57, 72
-  Euryale
-- range 65, 80
-  Xwin
-```
-
-# Screenshots
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/635567189c72a7e742f1419c/Cat8_Rimaz6Ni7YhQiiGB.png)
-
-# Benchmarks
-Coming soon.
-
-# Acknowledgements
-Credits goes to [@chargoddard](https://huggingface.co/chargoddard) for developing the framework used to merge the model - [mergekit](https://github.com/cg123/mergekit).
-
-Special thanks to [@Undi95](https://huggingface.co/Undi95) for helping with the merge ratios.
+2.64BPW @ 4096 ctx
+  Empty Ctx
+    GPU Split:18/24
+    GPU1: 19.8/24
+    GPU2: 21.9/24
+    10~ tk/s
+```