Usage of n_head to discriminate very small models

Of which the size is more sensitive to the non repeating tensors

Author: Nexesenex

src/llama.cpp

@@ -16441,14 +16441,15 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
 				else if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2) new_type = GGML_TYPE_Q4_K;
                 else new_type = GGML_TYPE_IQ4_XS;
             }
-            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_XL || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS) {
+            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_XL || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS ||
+			ftype == LLAMA_FTYPE_MOSTLY_IQ2_S) {
                 if (qs.model.hparams.n_expert >= 4) new_type = GGML_TYPE_Q6_K;
-                else if (qs.model.hparams.n_head <= 20) new_type = GGML_TYPE_IQ4_XS;
+                else if (qs.model.hparams.n_head() <= 20) new_type = GGML_TYPE_IQ4_XS;
                 else new_type = GGML_TYPE_Q4_K;
             }
-            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S  || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL) {
+            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_M || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL) {
                 if (qs.model.hparams.n_expert >= 4) new_type = GGML_TYPE_Q6_K;
-                else if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head <= 20) new_type = GGML_TYPE_Q4_K;
+                else if (qs.model.hparams.n_vocab >= 127999) new_type = GGML_TYPE_Q4_K;
                 else new_type = GGML_TYPE_Q5_K;
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS) {
@@ -16457,7 +16458,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_S  || ftype == LLAMA_FTYPE_MOSTLY_IQ3_M) {
                 if (qs.model.hparams.n_expert >= 4) new_type = GGML_TYPE_Q6_K;
-                else if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head <= 20) new_type = GGML_TYPE_Q5_K;
+                else if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head() <= 20) new_type = GGML_TYPE_Q5_K;
                 else new_type = GGML_TYPE_Q6_K;
             }
             else if (new_type != GGML_TYPE_Q8_0) {
@@ -16488,18 +16489,18 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
                 new_type = GGML_TYPE_IQ2_S;
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) {
-                if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head <= 20) new_type = GGML_TYPE_IQ2_S;
+                if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head() <= 20) new_type = GGML_TYPE_IQ2_S;
                 else new_type = GGML_TYPE_IQ3_XXS;
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) {
                 new_type = GGML_TYPE_IQ3_XXS;
             }
-            else if ( || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS) {
-                if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head <= 20) new_type = GGML_TYPE_IQ3_XXS;
+            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS) {
+                if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head() <= 20) new_type = GGML_TYPE_IQ3_XXS;
                 else new_type = GGML_TYPE_IQ3_S;
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXL) {
-                if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head <= 20) new_type = GGML_TYPE_IQ3_S;
+                if (qs.model.hparams.n_vocab >= 127999 || qs.model.hparams.n_head() <= 20) new_type = GGML_TYPE_IQ3_S;
                 new_type = GGML_TYPE_IQ4_XS;
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) new_type = GGML_TYPE_IQ3_XXS;