diff options
| -rw-r--r-- | llama.cpp | 69 |
1 files changed, 46 insertions, 23 deletions
@@ -356,17 +356,17 @@ struct llama_load_tensor { LLAMA_ASSERT(shards.size() <= UINT32_MAX); uint32_t n_shards = (uint32_t) shards.size(); switch (split_type) { - case SPLIT_NONE: - ne = first_shard.ne; - break; - case SPLIT_BY_COLUMNS: - ne = {checked_mul<uint32_t>(first_shard.ne[0], n_shards), - first_shard.ne[1]}; - break; - case SPLIT_BY_ROWS: - ne = {first_shard.ne[0], - checked_mul<uint32_t>(first_shard.ne[1], n_shards)}; - break; + case SPLIT_NONE: + ne = first_shard.ne; + break; + case SPLIT_BY_COLUMNS: + ne = {checked_mul<uint32_t>(first_shard.ne[0], n_shards), + first_shard.ne[1]}; + break; + case SPLIT_BY_ROWS: + ne = {first_shard.ne[0], + checked_mul<uint32_t>(first_shard.ne[1], n_shards)}; + break; } } @@ -806,6 +806,25 @@ bool llama_mlock_supported() { // model loading // +static const char *llama_file_version_name(llama_file_version version) { + switch (version) { + case LLAMA_FILE_VERSION_GGML: return "'ggml' (old version with low tokenizer quality and no mmap support)"; + case LLAMA_FILE_VERSION_GGMF_V1: return "ggmf v1 (old version with no mmap support)"; + case LLAMA_FILE_VERSION_GGJT_V1: return "ggjt v1 (latest)"; + default: LLAMA_ASSERT(false); + } +} + +static const char *llama_model_type_name(e_model type) { + switch (type) { + case MODEL_7B: return "7B"; + case MODEL_13B: return "13B"; + case MODEL_30B: return "30B"; + case MODEL_65B: return "65B"; + default: LLAMA_ASSERT(false); + } +} + static void llama_model_load_internal( const std::string & fname, llama_context & lctx, @@ -823,8 +842,9 @@ static void llama_model_load_internal( lctx.vocab = std::move(ml->file_loaders.at(0)->vocab); auto & model = lctx.model; + model.hparams = ml->file_loaders.at(0)->hparams; + llama_file_version file_version = ml->file_loaders.at(0)->file_version; auto & hparams = model.hparams; - hparams = ml->file_loaders.at(0)->hparams; uint32_t n_ff = ((2*(4*hparams.n_embd)/3 + hparams.n_mult - 1)/hparams.n_mult)*hparams.n_mult; { @@ -836,18 +856,21 @@ static void llama_model_load_internal( } hparams.n_ctx = n_ctx; + } - fprintf(stderr, "%s: n_vocab = %u\n", __func__, hparams.n_vocab); - fprintf(stderr, "%s: n_ctx = %u\n", __func__, hparams.n_ctx); - fprintf(stderr, "%s: n_embd = %u\n", __func__, hparams.n_embd); - fprintf(stderr, "%s: n_mult = %u\n", __func__, hparams.n_mult); - fprintf(stderr, "%s: n_head = %u\n", __func__, hparams.n_head); - fprintf(stderr, "%s: n_layer = %u\n", __func__, hparams.n_layer); - fprintf(stderr, "%s: n_rot = %u\n", __func__, hparams.n_rot); - fprintf(stderr, "%s: f16 = %u\n", __func__, hparams.f16); - fprintf(stderr, "%s: n_ff = %u\n", __func__, n_ff); - fprintf(stderr, "%s: n_parts = %zu\n", __func__, ml->file_loaders.size()); - fprintf(stderr, "%s: type = %u\n", __func__, model.type); + { + fprintf(stderr, "%s: format = %s\n", __func__, llama_file_version_name(file_version)); + fprintf(stderr, "%s: n_vocab = %u\n", __func__, hparams.n_vocab); + fprintf(stderr, "%s: n_ctx = %u\n", __func__, hparams.n_ctx); + fprintf(stderr, "%s: n_embd = %u\n", __func__, hparams.n_embd); + fprintf(stderr, "%s: n_mult = %u\n", __func__, hparams.n_mult); + fprintf(stderr, "%s: n_head = %u\n", __func__, hparams.n_head); + fprintf(stderr, "%s: n_layer = %u\n", __func__, hparams.n_layer); + fprintf(stderr, "%s: n_rot = %u\n", __func__, hparams.n_rot); + fprintf(stderr, "%s: f16 = %u\n", __func__, hparams.f16); + fprintf(stderr, "%s: n_ff = %u\n", __func__, n_ff); + fprintf(stderr, "%s: n_parts = %zu\n", __func__, ml->file_loaders.size()); + fprintf(stderr, "%s: model size = %s\n", __func__, llama_model_type_name(model.type)); } if (vocab_only) { |