return res;
}
+struct llama_context * llama_init_from_gpt_params(const gpt_params & params) {
+ auto lparams = llama_context_default_params();
+
+ lparams.n_ctx = params.n_ctx;
+ lparams.n_parts = params.n_parts;
+ lparams.seed = params.seed;
+ lparams.f16_kv = params.memory_f16;
+ lparams.use_mmap = params.use_mmap;
+ lparams.use_mlock = params.use_mlock;
+
+ llama_context * lctx = llama_init_from_file(params.model.c_str(), lparams);
+
+ if (lctx == NULL) {
+ fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
+ return NULL;
+ }
+
+ if (!params.lora_adapter.empty()) {
+ int err = llama_apply_lora_from_file(lctx,
+ params.lora_adapter.c_str(),
+ params.lora_base.empty() ? NULL : params.lora_base.c_str(),
+ params.n_threads);
+ if (err != 0) {
+ fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
+ return NULL;
+ }
+ }
+
+ return lctx;
+}
+
/* Keep track of current color of output, and emit ANSI code if it changes. */
void set_console_color(console_state & con_st, console_color_t color) {
if (con_st.use_color && con_st.color != color) {
std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::string & text, bool add_bos);
+//
+// Model utils
+//
+
+struct llama_context * llama_init_from_gpt_params(const gpt_params & params);
+
//
// Console utils
//
llama_context * ctx;
// load the model
- {
- auto lparams = llama_context_default_params();
-
- lparams.n_ctx = params.n_ctx;
- lparams.n_parts = params.n_parts;
- lparams.seed = params.seed;
- lparams.f16_kv = params.memory_f16;
- lparams.logits_all = params.perplexity;
- lparams.use_mmap = params.use_mmap;
- lparams.use_mlock = params.use_mlock;
- lparams.embedding = params.embedding;
-
- ctx = llama_init_from_file(params.model.c_str(), lparams);
-
- if (ctx == NULL) {
- fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
- return 1;
- }
+ ctx = llama_init_from_gpt_params(params);
+ if (ctx == NULL) {
+ fprintf(stderr, "%s: error: unable to load model\n", __func__);
+ return 1;
}
// print system information
llama_context * ctx;
g_ctx = &ctx;
- // load the model
- {
- auto lparams = llama_context_default_params();
-
- lparams.n_ctx = params.n_ctx;
- lparams.n_parts = params.n_parts;
- lparams.seed = params.seed;
- lparams.f16_kv = params.memory_f16;
- lparams.use_mmap = params.use_mmap;
- lparams.use_mlock = params.use_mlock;
-
- ctx = llama_init_from_file(params.model.c_str(), lparams);
-
- if (ctx == NULL) {
- fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
- return 1;
- }
- }
-
- if (!params.lora_adapter.empty()) {
- int err = llama_apply_lora_from_file(ctx,
- params.lora_adapter.c_str(),
- params.lora_base.empty() ? NULL : params.lora_base.c_str(),
- params.n_threads);
- if (err != 0) {
- fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
- return 1;
- }
+ // load the model and apply lora adapter, if any
+ ctx = llama_init_from_gpt_params(params);
+ if (ctx == NULL) {
+ fprintf(stderr, "%s: error: unable to load model\n", __func__);
+ return 1;
}
// print system information
llama_context * ctx;
- // load the model
- {
- auto lparams = llama_context_default_params();
-
- lparams.n_ctx = params.n_ctx;
- lparams.n_parts = params.n_parts;
- lparams.seed = params.seed;
- lparams.f16_kv = params.memory_f16;
- lparams.logits_all = params.perplexity;
- lparams.use_mmap = params.use_mmap;
- lparams.use_mlock = params.use_mlock;
- lparams.embedding = params.embedding;
-
- ctx = llama_init_from_file(params.model.c_str(), lparams);
-
- if (ctx == NULL) {
- fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
- return 1;
- }
- }
-
- if (!params.lora_adapter.empty()) {
- int err = llama_apply_lora_from_file(ctx,
- params.lora_adapter.c_str(),
- params.lora_base.empty() ? NULL : params.lora_base.c_str(),
- params.n_threads);
- if (err != 0) {
- fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
- return 1;
- }
+ // load the model and apply lora adapter, if any
+ ctx = llama_init_from_gpt_params(params);
+ if (ctx == NULL) {
+ fprintf(stderr, "%s: error: unable to load model\n", __func__);
+ return 1;
}
// print system information