Removed support for GGML_TYPE_Q4_0_4_4, GGML_TYPE_0_4_8, and GGML_TYPE_0_8_8 (GGUF no longer supports these types)
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+3
-24
@@ -4843,9 +4843,7 @@ struct llama_model_loader {
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case GGML_TYPE_IQ4_NL: ftype = LLAMA_FTYPE_MOSTLY_IQ4_NL; break;
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case GGML_TYPE_IQ4_XS: ftype = LLAMA_FTYPE_MOSTLY_IQ4_XS; break;
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case GGML_TYPE_IQ3_S: ftype = LLAMA_FTYPE_MOSTLY_IQ3_S; break;
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case GGML_TYPE_Q4_0_4_4: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_4; break;
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case GGML_TYPE_Q4_0_4_8: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_8; break;
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case GGML_TYPE_Q4_0_8_8: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_8_8; break;
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default:
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{
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LLAMA_LOG_WARN("%s: unknown type %s\n", __func__, ggml_type_name(type_max));
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@@ -5653,9 +5651,6 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
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case LLAMA_FTYPE_MOSTLY_IQ4_XS: return "IQ4_XS - 4.25 bpw";
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case LLAMA_FTYPE_MOSTLY_IQ3_S: return "IQ3_S - 3.4375 bpw";
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case LLAMA_FTYPE_MOSTLY_IQ3_M: return "IQ3_S mix - 3.66 bpw";
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case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: return "Q4_0_4_4";
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case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: return "Q4_0_4_8";
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case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: return "Q4_0_8_8";
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default: return "unknown, may not work";
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}
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@@ -18996,10 +18991,6 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
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else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) {
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new_type = GGML_TYPE_IQ3_S;
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}
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else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 ||
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new_type == GGML_TYPE_Q4_0_8_8) {
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new_type = GGML_TYPE_Q4_0;
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}
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else if (ftype == LLAMA_FTYPE_MOSTLY_TQ1_0 || ftype == LLAMA_FTYPE_MOSTLY_TQ2_0) {
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new_type = GGML_TYPE_Q4_K;
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}
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@@ -19322,10 +19313,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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case LLAMA_FTYPE_MOSTLY_IQ4_XS: default_type = GGML_TYPE_IQ4_XS; break;
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case LLAMA_FTYPE_MOSTLY_IQ3_S: default_type = GGML_TYPE_IQ3_S; break;
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case LLAMA_FTYPE_MOSTLY_IQ3_M: default_type = GGML_TYPE_IQ3_S; break;
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case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: default_type = GGML_TYPE_Q4_0_4_4; break;
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case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: default_type = GGML_TYPE_Q4_0_4_8; break;
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case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: default_type = GGML_TYPE_Q4_0_8_8; break;
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default: throw std::runtime_error(format("invalid output file type %d\n", ftype));
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}
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@@ -19645,14 +19633,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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f32_data = (float *) f32_conv_buf.data();
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}
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int chunk_size_multiplier = 1;
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if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 || new_type == GGML_TYPE_Q4_0_8_8) {
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if ((new_type == GGML_TYPE_Q4_0_8_8) && (tensor->ne[1] % 8 != 0)) new_type = GGML_TYPE_Q4_0;
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else if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q4_0;
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if (new_type == GGML_TYPE_Q4_0_8_8) chunk_size_multiplier = 8;
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else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8) chunk_size_multiplier = 4;
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}
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LLAMA_LOG_INFO("converting to %s .. ", ggml_type_name(new_type));
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fflush(stdout);
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@@ -19665,8 +19645,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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const int64_t nrows = tensor->ne[1];
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static const int64_t min_chunk_size = 32 * 512;
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const int64_t chunk_size = (n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row)) *
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chunk_size_multiplier;
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const int64_t chunk_size = (n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row));
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const int64_t nelements_matrix = tensor->ne[0] * tensor->ne[1];
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const int64_t nchunk = (nelements_matrix + chunk_size - 1)/chunk_size;
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