Update README.md

README.md

@@ -1,6 +1,7 @@
 ---
 license: apache-2.0
 tags:
+- not-for-all-audiences
 - GGUF
 - merge
 - iMat
@@ -31,11 +32,18 @@ Quantized from fp16 with love.
 
 For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747)
 
-<i>All quants are verified working prior to uploading to repo for your safety and convenience. </i>
+<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, IQ3 and above is recommended for best results. 
 
-<b>Tip:</b> Pick a size that can fit in your GPU while still allowing some room for context for best speed. You may need to pad this further depending on if you are running image gen or TTS as well.
+<b>Tip:</b> Pick a size in the table below that can fit in your GPU while still allowing some room for context for best speed. You may need to pad this further depending on if you are running image gen or TTS as well.
+
+| Quant | Size (GB) | Comments |
+|:-----|--------:|:------|
+| [IQ4_XS](https://huggingface.co/Quant-Cartel/Cerebrum-1.0-8x7b-iMat-GGUF/blob/main/Cerebrum-1.0-8x7b-iMat-IQ4_XS.gguf) |  25.1 |  Better quality than Q3_K_L and below |
+| [Q4_K_M ](https://huggingface.co/Quant-Cartel/Cerebrum-1.0-8x7b-iMat-GGUF/blob/main/Cerebrum-1.0-8x7b-iMat-Q4_K_M.gguf) |  28.4 | |
+| [Q5_K_M ](https://huggingface.co/Quant-Cartel/Cerebrum-1.0-8x7b-iMat-GGUF/blob/main/Cerebrum-1.0-8x7b-iMat-Q5_K_M.gguf) |  33.2 | |
+
 
 Original model card can be found [here](https://huggingface.co/AetherResearch/Cerebrum-1.0-8x7b) and below.