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examples : add llama_init_from_gpt_params() common function (#1290)
Signed-off-by: deadprogram <ron@hybridgroup.com>
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@ -405,6 +405,37 @@ std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::s
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return res;
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}
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struct llama_context * llama_init_from_gpt_params(const gpt_params & params) {
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auto lparams = llama_context_default_params();
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lparams.n_ctx = params.n_ctx;
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lparams.n_parts = params.n_parts;
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lparams.seed = params.seed;
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lparams.f16_kv = params.memory_f16;
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lparams.use_mmap = params.use_mmap;
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lparams.use_mlock = params.use_mlock;
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llama_context * lctx = llama_init_from_file(params.model.c_str(), lparams);
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if (lctx == NULL) {
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fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
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return NULL;
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}
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if (!params.lora_adapter.empty()) {
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int err = llama_apply_lora_from_file(lctx,
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params.lora_adapter.c_str(),
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params.lora_base.empty() ? NULL : params.lora_base.c_str(),
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params.n_threads);
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if (err != 0) {
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fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
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return NULL;
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}
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}
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return lctx;
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}
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/* Keep track of current color of output, and emit ANSI code if it changes. */
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void set_console_color(console_state & con_st, console_color_t color) {
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if (con_st.use_color && con_st.color != color) {
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@ -77,6 +77,12 @@ std::string gpt_random_prompt(std::mt19937 & rng);
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std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::string & text, bool add_bos);
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//
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// Model utils
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//
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struct llama_context * llama_init_from_gpt_params(const gpt_params & params);
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//
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// Console utils
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//
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@ -35,24 +35,10 @@ int main(int argc, char ** argv) {
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llama_context * ctx;
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// load the model
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{
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auto lparams = llama_context_default_params();
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lparams.n_ctx = params.n_ctx;
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lparams.n_parts = params.n_parts;
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lparams.seed = params.seed;
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lparams.f16_kv = params.memory_f16;
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lparams.logits_all = params.perplexity;
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lparams.use_mmap = params.use_mmap;
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lparams.use_mlock = params.use_mlock;
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lparams.embedding = params.embedding;
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ctx = llama_init_from_file(params.model.c_str(), lparams);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
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return 1;
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}
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ctx = llama_init_from_gpt_params(params);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: unable to load model\n", __func__);
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return 1;
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}
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// print system information
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@ -101,34 +101,11 @@ int main(int argc, char ** argv) {
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llama_context * ctx;
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g_ctx = &ctx;
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// load the model
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{
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auto lparams = llama_context_default_params();
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lparams.n_ctx = params.n_ctx;
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lparams.n_parts = params.n_parts;
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lparams.seed = params.seed;
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lparams.f16_kv = params.memory_f16;
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lparams.use_mmap = params.use_mmap;
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lparams.use_mlock = params.use_mlock;
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ctx = llama_init_from_file(params.model.c_str(), lparams);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
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return 1;
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}
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}
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if (!params.lora_adapter.empty()) {
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int err = llama_apply_lora_from_file(ctx,
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params.lora_adapter.c_str(),
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params.lora_base.empty() ? NULL : params.lora_base.c_str(),
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params.n_threads);
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if (err != 0) {
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fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
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return 1;
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}
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// load the model and apply lora adapter, if any
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ctx = llama_init_from_gpt_params(params);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: unable to load model\n", __func__);
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return 1;
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}
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// print system information
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@ -122,36 +122,11 @@ int main(int argc, char ** argv) {
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llama_context * ctx;
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// load the model
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{
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auto lparams = llama_context_default_params();
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lparams.n_ctx = params.n_ctx;
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lparams.n_parts = params.n_parts;
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lparams.seed = params.seed;
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lparams.f16_kv = params.memory_f16;
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lparams.logits_all = params.perplexity;
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lparams.use_mmap = params.use_mmap;
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lparams.use_mlock = params.use_mlock;
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lparams.embedding = params.embedding;
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ctx = llama_init_from_file(params.model.c_str(), lparams);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
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return 1;
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}
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}
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if (!params.lora_adapter.empty()) {
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int err = llama_apply_lora_from_file(ctx,
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params.lora_adapter.c_str(),
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params.lora_base.empty() ? NULL : params.lora_base.c_str(),
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params.n_threads);
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if (err != 0) {
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fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
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return 1;
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}
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// load the model and apply lora adapter, if any
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ctx = llama_init_from_gpt_params(params);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: unable to load model\n", __func__);
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return 1;
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}
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// print system information
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