metadata: use char* under the hood to avoid conversion round trips
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3952a221af
commit
17a800be68
5 changed files with 23 additions and 40 deletions
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@ -422,8 +422,7 @@ int main(int argc, char ** argv) {
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int n_layers = llama_n_layer(model);
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int n_layers = llama_n_layer(model);
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int n_embd = llama_n_embd(model);
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int n_embd = llama_n_embd(model);
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// get model hint param (a.k.a model arch name)
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// get model hint param (a.k.a model arch name)
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char model_hint[128];
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const char* model_hint = llama_model_meta_val_str(model, "general.architecture");
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llama_model_meta_val_str(model, "general.architecture", model_hint, 128);
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// init train_context
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// init train_context
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train_context ctx_train(n_embd, n_layers);
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train_context ctx_train(n_embd, n_layers);
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@ -663,15 +663,14 @@ struct server_context {
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bool validate_model_chat_template() const {
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bool validate_model_chat_template() const {
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std::vector<char> model_template(2048, 0); // longest known template is about 1200 bytes
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std::vector<char> model_template(2048, 0); // longest known template is about 1200 bytes
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std::string template_key = "tokenizer.chat_template";
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std::string template_key = "tokenizer.chat_template";
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int32_t res = llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), model_template.size());
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const char* tmpl = llama_model_meta_val_str(model, template_key.c_str());
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if (res >= 0) {
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if (tmpl == NULL) {
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llama_chat_message chat[] = {{"user", "test"}};
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std::string tmpl = std::string(model_template.data(), model_template.size());
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int32_t chat_res = llama_chat_apply_template(model, tmpl.c_str(), chat, 1, true, nullptr, 0);
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return chat_res > 0;
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}
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return false;
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return false;
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}
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}
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llama_chat_message chat[] = {{"user", "test"}};
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int32_t chat_res = llama_chat_apply_template(model, tmpl, chat, 1, true, nullptr, 0);
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return chat_res > 0;
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}
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void init() {
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void init() {
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const int32_t n_ctx_slot = n_ctx / params.n_parallel;
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const int32_t n_ctx_slot = n_ctx / params.n_parallel;
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@ -336,15 +336,8 @@ inline std::string format_chat(const struct llama_model * model, const std::stri
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static std::string llama_get_chat_template(const struct llama_model * model) {
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static std::string llama_get_chat_template(const struct llama_model * model) {
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std::string template_key = "tokenizer.chat_template";
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std::string template_key = "tokenizer.chat_template";
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// call with NULL buffer to get the total size of the string
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const char* tmpl = llama_model_meta_val_str(model, template_key.c_str());
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int32_t res = llama_model_meta_val_str(model, template_key.c_str(), NULL, 0);
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return tmpl ? tmpl : "";
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if (res < 0) {
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return "";
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} else {
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std::vector<char> model_template(res, 0);
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llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), model_template.size());
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return std::string(model_template.data(), model_template.size());
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}
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}
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}
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//
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//
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@ -449,12 +449,11 @@ extern "C" {
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LLAMA_API float llama_rope_freq_scale_train(const struct llama_model * model);
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LLAMA_API float llama_rope_freq_scale_train(const struct llama_model * model);
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// Functions to access the model's GGUF metadata scalar values
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// Functions to access the model's GGUF metadata scalar values
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// - The functions return the length of the string on success, or -1 on failure
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// - The functions return a const char* of the value on success, and NULL on failure.
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// - The output string is always null-terminated and cleared on failure
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// - GGUF array values are not supported by these functions
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// - GGUF array values are not supported by these functions
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// Get metadata value as a string by key name
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// Get metadata value as a string by key name
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LLAMA_API int32_t llama_model_meta_val_str(const struct llama_model * model, const char * key, char * buf, size_t buf_size);
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LLAMA_API const char* llama_model_meta_val_str(const struct llama_model * model, const char * key);
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// Get the number of metadata key/value pairs
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// Get the number of metadata key/value pairs
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LLAMA_API int32_t llama_model_meta_count(const struct llama_model * model);
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LLAMA_API int32_t llama_model_meta_count(const struct llama_model * model);
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@ -463,7 +462,7 @@ extern "C" {
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LLAMA_API int32_t llama_model_meta_key_by_index(const struct llama_model * model, int32_t i, char * buf, size_t buf_size);
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LLAMA_API int32_t llama_model_meta_key_by_index(const struct llama_model * model, int32_t i, char * buf, size_t buf_size);
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// Get metadata value as a string by index
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// Get metadata value as a string by index
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LLAMA_API int32_t llama_model_meta_val_str_by_index(const struct llama_model * model, int32_t i, char * buf, size_t buf_size);
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LLAMA_API const char* llama_model_meta_val_str_by_index(const struct llama_model * model, int32_t i);
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// Get a string describing the model type
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// Get a string describing the model type
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LLAMA_API int32_t llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size);
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LLAMA_API int32_t llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size);
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@ -2887,7 +2887,7 @@ struct llama_model {
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std::vector<llama_layer> layers;
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std::vector<llama_layer> layers;
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// gguf metadata
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// gguf metadata
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std::unordered_map<std::string, std::string> gguf_kv;
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std::unordered_map<std::string, char*> gguf_kv;
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llama_split_mode split_mode;
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llama_split_mode split_mode;
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int main_gpu;
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int main_gpu;
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@ -5389,7 +5389,7 @@ static void llm_load_hparams(
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}
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}
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const char * name = gguf_get_key(ctx, i);
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const char * name = gguf_get_key(ctx, i);
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const std::string value = gguf_kv_to_str(ctx, i);
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const std::string value = gguf_kv_to_str(ctx, i);
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model.gguf_kv.emplace(name, value);
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model.gguf_kv.emplace(name, strdup(value.c_str()));
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}
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}
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// get general kv
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// get general kv
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@ -20097,15 +20097,12 @@ float llama_rope_freq_scale_train(const struct llama_model * model) {
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return model->hparams.rope_freq_scale_train;
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return model->hparams.rope_freq_scale_train;
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}
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}
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int32_t llama_model_meta_val_str(const struct llama_model * model, const char * key, char * buf, size_t buf_size) {
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const char* llama_model_meta_val_str(const struct llama_model * model, const char * key) {
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const auto & it = model->gguf_kv.find(key);
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const auto & it = model->gguf_kv.find(key);
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if (it == model->gguf_kv.end()) {
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if (it == model->gguf_kv.end()) {
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if (buf_size > 0) {
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return NULL;
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buf[0] = '\0';
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}
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}
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return -1;
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return it->second;
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}
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return snprintf(buf, buf_size, "%s", it->second.c_str());
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}
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}
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int32_t llama_model_meta_count(const struct llama_model * model) {
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int32_t llama_model_meta_count(const struct llama_model * model) {
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@ -20124,16 +20121,13 @@ int32_t llama_model_meta_key_by_index(const struct llama_model * model, int i, c
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return snprintf(buf, buf_size, "%s", it->first.c_str());
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return snprintf(buf, buf_size, "%s", it->first.c_str());
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}
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}
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int32_t llama_model_meta_val_str_by_index(const struct llama_model * model, int32_t i, char * buf, size_t buf_size) {
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const char* llama_model_meta_val_str_by_index(const struct llama_model * model, int32_t i) {
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if (i < 0 || i >= (int)model->gguf_kv.size()) {
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if (i < 0 || i >= (int)model->gguf_kv.size()) {
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if (buf_size > 0) {
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return NULL;
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buf[0] = '\0';
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}
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return -1;
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}
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}
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auto it = model->gguf_kv.begin();
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auto it = model->gguf_kv.begin();
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std::advance(it, i);
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std::advance(it, i);
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return snprintf(buf, buf_size, "%s", it->second.c_str());
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return it->second;
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}
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}
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int32_t llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size) {
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int32_t llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size) {
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@ -22116,14 +22110,13 @@ int32_t llama_chat_apply_template(
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if (tmpl == nullptr) {
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if (tmpl == nullptr) {
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GGML_ASSERT(model != nullptr);
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GGML_ASSERT(model != nullptr);
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// load template from model
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// load template from model
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std::vector<char> model_template(2048, 0); // longest known template is about 1200 bytes
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std::string template_key = "tokenizer.chat_template";
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std::string template_key = "tokenizer.chat_template";
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int32_t res = llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), model_template.size());
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const char* tmpl = llama_model_meta_val_str(model, template_key.c_str());
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if (res < 0) {
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if (tmpl == NULL) {
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// worst case: there is no information about template, we will use chatml by default
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// worst case: there is no information about template, we will use chatml by default
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curr_tmpl = "chatml"; // see llama_chat_apply_template_internal
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curr_tmpl = "chatml"; // see llama_chat_apply_template_internal
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} else {
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} else {
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curr_tmpl = std::string(model_template.data(), model_template.size());
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curr_tmpl = tmpl;
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}
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}
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}
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}
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