From 16bc66d9479edd5ee12ec734973554d4493c5dfa Mon Sep 17 00:00:00 2001 From: slaren Date: Thu, 28 Sep 2023 21:42:38 +0200 Subject: llama.cpp : split llama_context_params into model and context params (#3301) * llama.cpp : split llama_context_params into model and context params ggml-ci * fix metal build * fix freq_base/scale default to model value * llama-bench : keep the same model between tests when possible * move n_threads to llama_context_params, add n_threads_batch * fix mpi build * remove kv_size(), cuda scratch fixes * remove low-vram option * add n_threads_batch to system info, refactor to get_system_info() * add documentation about --threads-batch to the READMEs * llama-bench fix * main : fix rope freq/scale warning * llama.cpp : add llama_get_model common : add llama_tokenize from model * remove duplicated ctx/model functions ggml-ci * cuda : print total VRAM used --- tests/test-tokenizer-0-falcon.cpp | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) (limited to 'tests/test-tokenizer-0-falcon.cpp') diff --git a/tests/test-tokenizer-0-falcon.cpp b/tests/test-tokenizer-0-falcon.cpp index 836fb8ad..d51851e2 100644 --- a/tests/test-tokenizer-0-falcon.cpp +++ b/tests/test-tokenizer-0-falcon.cpp @@ -62,18 +62,20 @@ int main(int argc, char **argv) { // load the vocab { - auto lparams = llama_context_default_params(); + auto mparams = llama_model_default_params(); - lparams.vocab_only = true; + mparams.vocab_only = true; - model = llama_load_model_from_file(fname.c_str(), lparams); + model = llama_load_model_from_file(fname.c_str(), mparams); if (model == NULL) { fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); return 1; } - ctx = llama_new_context_with_model(model, lparams); + auto cparams = llama_context_default_params(); + + ctx = llama_new_context_with_model(model, cparams); if (ctx == NULL) { fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); @@ -82,7 +84,7 @@ int main(int argc, char **argv) { } } - if (llama_vocab_type(ctx) != LLAMA_VOCAB_TYPE_BPE) { + if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_BPE) { fprintf(stderr, "%s : error: vocab type is not SPM\n", __func__); llama_free_model(model); llama_free(ctx); -- cgit v1.2.3