1 files changed, 9 insertions, 1 deletions

diff --git a/llama.cpp b/llama.cpp
index 3ff5dc1e..99d29a1e 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -479,6 +479,7 @@ struct llama_file_loader {
                 case GGML_TYPE_Q4_0:
                 case GGML_TYPE_Q4_1:
                 case GGML_TYPE_Q4_2:
+                case GGML_TYPE_Q4_3:
                     break;
                 default: {
                     throw format("unrecognized tensor type %u\n", shard.type);
@@ -552,6 +553,7 @@ struct llama_file_saver {
             case GGML_TYPE_Q4_0:
             case GGML_TYPE_Q4_1:
             case GGML_TYPE_Q4_2:
+            case GGML_TYPE_Q4_3:
                 break;
             default: LLAMA_ASSERT(false);
         }
@@ -841,6 +843,7 @@ static const char *llama_ftype_name(enum llama_ftype ftype) {
         case LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16:
                                       return "mostly Q4_1, some F16";
         case LLAMA_FTYPE_MOSTLY_Q4_2: return "mostly Q4_2";
+        case LLAMA_FTYPE_MOSTLY_Q4_3: return "mostly Q4_3";
         default:                      return "unknown, may not work";
     }
 }
@@ -1575,6 +1578,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
         case LLAMA_FTYPE_MOSTLY_Q4_0: quantized_type = GGML_TYPE_Q4_0; break;
         case LLAMA_FTYPE_MOSTLY_Q4_1: quantized_type = GGML_TYPE_Q4_1; break;
         case LLAMA_FTYPE_MOSTLY_Q4_2: quantized_type = GGML_TYPE_Q4_2; break;
+        case LLAMA_FTYPE_MOSTLY_Q4_3: quantized_type = GGML_TYPE_Q4_3; break;
         default: throw format("invalid output file type %d\n", ftype);
     };
 
@@ -1652,6 +1656,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
                     {
                         new_size = ggml_quantize_q4_2(f32_data, new_data, nelements, (int) tensor.ne.at(0), hist_cur.data());
                     } break;
+                case GGML_TYPE_Q4_3:
+                    {
+                        new_size = ggml_quantize_q4_3(f32_data, new_data, nelements, (int) tensor.ne.at(0), hist_cur.data());
+                    } break;
                 default:
                     LLAMA_ASSERT(false);
             }
@@ -1963,7 +1971,7 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
                 base_t = dest_t;
             }
 
-            if (base_t->type == GGML_TYPE_Q4_0 || base_t->type == GGML_TYPE_Q4_1 || base_t->type == GGML_TYPE_Q4_2) {
+            if (ggml_is_quantized(base_t->type)) {
                 if (!warned) {
                     fprintf(stderr, "%s: warning: using a lora adapter with a quantized model may result in poor quality, "
                                     "use a f16 or f32 base model with --lora-base\n", __func__);