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https://github.com/ggerganov/llama.cpp.git
synced 2024-10-30 06:30:15 +01:00
Print model version.
Also improve model type printing, and fix indentation of an unrelated switch statement.
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parent
f963b63afa
commit
180b693a47
69
llama.cpp
69
llama.cpp
@ -356,17 +356,17 @@ struct llama_load_tensor {
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LLAMA_ASSERT(shards.size() <= UINT32_MAX);
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uint32_t n_shards = (uint32_t) shards.size();
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switch (split_type) {
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case SPLIT_NONE:
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ne = first_shard.ne;
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break;
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case SPLIT_BY_COLUMNS:
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ne = {checked_mul<uint32_t>(first_shard.ne[0], n_shards),
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first_shard.ne[1]};
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break;
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case SPLIT_BY_ROWS:
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ne = {first_shard.ne[0],
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checked_mul<uint32_t>(first_shard.ne[1], n_shards)};
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break;
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case SPLIT_NONE:
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ne = first_shard.ne;
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break;
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case SPLIT_BY_COLUMNS:
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ne = {checked_mul<uint32_t>(first_shard.ne[0], n_shards),
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first_shard.ne[1]};
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break;
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case SPLIT_BY_ROWS:
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ne = {first_shard.ne[0],
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checked_mul<uint32_t>(first_shard.ne[1], n_shards)};
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break;
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}
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}
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@ -806,6 +806,25 @@ bool llama_mlock_supported() {
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// model loading
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//
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static const char *llama_file_version_name(llama_file_version version) {
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switch (version) {
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case LLAMA_FILE_VERSION_GGML: return "'ggml' (old version with low tokenizer quality and no mmap support)";
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case LLAMA_FILE_VERSION_GGMF_V1: return "ggmf v1 (old version with no mmap support)";
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case LLAMA_FILE_VERSION_GGJT_V1: return "ggjt v1 (latest)";
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default: LLAMA_ASSERT(false);
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}
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}
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static const char *llama_model_type_name(e_model type) {
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switch (type) {
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case MODEL_7B: return "7B";
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case MODEL_13B: return "13B";
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case MODEL_30B: return "30B";
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case MODEL_65B: return "65B";
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default: LLAMA_ASSERT(false);
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}
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}
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static void llama_model_load_internal(
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const std::string & fname,
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llama_context & lctx,
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@ -823,8 +842,9 @@ static void llama_model_load_internal(
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lctx.vocab = std::move(ml->file_loaders.at(0)->vocab);
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auto & model = lctx.model;
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model.hparams = ml->file_loaders.at(0)->hparams;
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llama_file_version file_version = ml->file_loaders.at(0)->file_version;
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auto & hparams = model.hparams;
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hparams = ml->file_loaders.at(0)->hparams;
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uint32_t n_ff = ((2*(4*hparams.n_embd)/3 + hparams.n_mult - 1)/hparams.n_mult)*hparams.n_mult;
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{
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@ -836,18 +856,21 @@ static void llama_model_load_internal(
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}
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hparams.n_ctx = n_ctx;
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}
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fprintf(stderr, "%s: n_vocab = %u\n", __func__, hparams.n_vocab);
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fprintf(stderr, "%s: n_ctx = %u\n", __func__, hparams.n_ctx);
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fprintf(stderr, "%s: n_embd = %u\n", __func__, hparams.n_embd);
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fprintf(stderr, "%s: n_mult = %u\n", __func__, hparams.n_mult);
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fprintf(stderr, "%s: n_head = %u\n", __func__, hparams.n_head);
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fprintf(stderr, "%s: n_layer = %u\n", __func__, hparams.n_layer);
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fprintf(stderr, "%s: n_rot = %u\n", __func__, hparams.n_rot);
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fprintf(stderr, "%s: f16 = %u\n", __func__, hparams.f16);
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fprintf(stderr, "%s: n_ff = %u\n", __func__, n_ff);
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fprintf(stderr, "%s: n_parts = %zu\n", __func__, ml->file_loaders.size());
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fprintf(stderr, "%s: type = %u\n", __func__, model.type);
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{
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fprintf(stderr, "%s: format = %s\n", __func__, llama_file_version_name(file_version));
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fprintf(stderr, "%s: n_vocab = %u\n", __func__, hparams.n_vocab);
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fprintf(stderr, "%s: n_ctx = %u\n", __func__, hparams.n_ctx);
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fprintf(stderr, "%s: n_embd = %u\n", __func__, hparams.n_embd);
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fprintf(stderr, "%s: n_mult = %u\n", __func__, hparams.n_mult);
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fprintf(stderr, "%s: n_head = %u\n", __func__, hparams.n_head);
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fprintf(stderr, "%s: n_layer = %u\n", __func__, hparams.n_layer);
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fprintf(stderr, "%s: n_rot = %u\n", __func__, hparams.n_rot);
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fprintf(stderr, "%s: f16 = %u\n", __func__, hparams.f16);
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fprintf(stderr, "%s: n_ff = %u\n", __func__, n_ff);
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fprintf(stderr, "%s: n_parts = %zu\n", __func__, ml->file_loaders.size());
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fprintf(stderr, "%s: model size = %s\n", __func__, llama_model_type_name(model.type));
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}
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if (vocab_only) {
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