Update README.md

README.md

@@ -15,7 +15,7 @@ And a bonus to play with it, my KoboldCPP_-_v1.55.1.b1933_-_Frankenstein from th
 
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-Edit : Due to a poor CPU (i7-6700k) for AI purpose, and only 36GB of VRAM, I remade Q3_K_S and Q2_K with an small iMatrix of ctx 32 with 25 chunks (so, 640 tokens).
+Edit : Due to a poor CPU (i7-6700k) for AI purpose, and only 36GB of VRAM, I remade Q3_K_S and Q2_K with an small iMatrix of ctx 32 with 25 chunks (so, 800 tokens).
 And good news, it lowers the perplexity by :
 
 More than 3% with linear rope 8 (Pos Compress Embeddings) on Q2_K
@@ -34,13 +34,17 @@ More than 1% with linear rope 8 on Q3_K_S
 - WinterGoddess-1.4x-limarpv3-70B-L2-32k-Requant-AR-b1924-Q3_K_S.gguf,-,wikitext,5.6127,512 
 - WinterGoddess-1.4x-limarpv3-70B-L2-32k-Requant-AR-b1924-iMat-c32_ch25-Q3_K_S.gguf,-,wikitext,5.5461,512
 
-A Q3_K_M with iMatrix has been added as well, and a Q2_K_S is otw.
+A Q3_K_M with iMatrix has been added as well, as well as a Q2_K_S.
 
 Rope 2.5 :
 - WinterGoddess-1.4x-limarpv3-70B-L2-32k-Requant-AR-b1924-iMat-c32_ch25-Q2_K_S.gguf,-,wikitext,4.6789,512
 
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+Edit : A Q3_K_XS, new quant offered in LlamaCPP, is otw, with a iMatrix of ctx 32 with 2500 chunks (so, 80,000 tokens)
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 Interestingly, linear rope 2.5 (and linear rope 1.6 as well after further testing) is almost without loss compared to linear rope 2, while 3 and 3.2 are quite good. Here are the values with the normal Q2_K :
 
 - Linear rope 2.5 (max context 10240) : WinterGoddess-1.4x-limarpv3-70B-L2-32k-Requant-AR-b1924-Q2_K.gguf,-,wikitext,4.5246,512