Update README.md

README.md

@@ -12,6 +12,7 @@ Quantized from fp16.
 * Weighted quantizations were creating using fp16 GGUF and [groups_merged-enhancedV2-TurboMini.txt](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-9432658) in 234 chunks and n_ctx=512
 * This method of calculating the importance matrix showed improvements in some areas for Mistral 7b and Llama3 8b models, see above post for details
 * The enhancedv2-turbomini file appends snippets from turboderp's calibration data to the standard groups_merged.txt file
+* Repetition penalty 1.05-1.15 has worked well for these quants. 
 
 For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747)