Merge branch 'upstream' into concedo_experimental

# Conflicts:
#	.github/workflows/build-self-hosted.yml
#	.github/workflows/build.yml
#	.github/workflows/copilot-setup-steps.yml
#	.github/workflows/gguf-publish.yml
#	ci/run.sh
#	docs/backend/OPENVINO.md
#	examples/llama.android/lib/src/main/cpp/ai_chat.cpp
#	ggml/src/ggml-sycl/add-id.cpp
#	requirements/requirements-pydantic.txt
#	tests/test-gguf.cpp
#	tests/test-jinja.cpp
#	tests/test-llama-archs.cpp
#	tools/gguf-split/README.md
#	tools/llama-bench/llama-bench.cpp

src/llama.cpp

@@ -851,7 +851,7 @@ int64_t llama_time_us(void) {
 
 // Returns 0 on success, -1 on error, and -2 on cancellation via llama_progress_callback
 static int llama_model_load(struct gguf_context * metadata, llama_model_set_tensor_data_t set_tensor_data, void * set_tensor_data_ud,
-        const std::string & fname, std::vector<std::string> & splits, llama_model & model, llama_model_params & params) {
+        const std::string & fname, std::vector<std::string> & splits, FILE * file, llama_model & model, llama_model_params & params) {
     // loading time will be recalculated after the first eval, so
     // we take page faults deferred by mmap() into consideration
     model.t_load_us = 0;
@@ -860,7 +860,7 @@ static int llama_model_load(struct gguf_context * metadata, llama_model_set_tens
     model.t_start_us = tm.t_start_us;
 
     try {
-        llama_model_loader ml(metadata, set_tensor_data, set_tensor_data_ud, fname, splits, params.use_mmap, params.use_direct_io,
+        llama_model_loader ml(metadata, set_tensor_data, set_tensor_data_ud, fname, splits, file, params.use_mmap, params.use_direct_io,
             params.check_tensors, params.no_alloc, params.kv_overrides, params.tensor_buft_overrides);
 
         ml.print_info();
@@ -912,8 +912,24 @@ static struct llama_model * llama_model_load_from_file_impl(
         void * set_tensor_data_ud,
         const std::string & path_model,
         std::vector<std::string> & splits,
+        FILE * file,
         struct llama_model_params params) {
-    GGML_ASSERT((metadata == nullptr) != path_model.empty() && "exactly one out of metadata and path_model needs to be defined");
+    {
+        int n_sources_defined = 0;
+        if (metadata != nullptr) {
+            n_sources_defined++;
+        }
+        if (!path_model.empty()) {
+            n_sources_defined++;
+        }
+        if (file != nullptr) {
+            n_sources_defined++;
+        }
+        if (n_sources_defined != 1) {
+            LLAMA_LOG_ERROR("%s: exactly one out metadata, path_model, and file must be defined\n", __func__);
+            return nullptr;
+        }
+    }
     ggml_time_init();
 
     if (!params.vocab_only && ggml_backend_reg_count() == 0) {
@@ -1034,7 +1050,7 @@ static struct llama_model * llama_model_load_from_file_impl(
                 props.memory_free/1024/1024);
     }
 
-    const int status = llama_model_load(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, *model, params);
+    const int status = llama_model_load(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, file, *model, params);
     GGML_ASSERT(status <= 0);
     if (status < 0) {
         if (status == -1) {
@@ -1060,7 +1076,7 @@ struct llama_model * llama_model_init_from_user(
     std::vector<std::string> splits = {};
     params.use_mmap = false;
     params.use_extra_bufts = false;
-    return llama_model_load_from_file_impl(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, params);
+    return llama_model_load_from_file_impl(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, /*file*/ nullptr, params);
 }
 // deprecated
 struct llama_model * llama_load_model_from_file(
@@ -1073,7 +1089,7 @@ struct llama_model * llama_model_load_from_file(
         const char * path_model,
         struct llama_model_params params) {
     std::vector<std::string> splits = {};
-    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, path_model, splits, params);
+    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, path_model, splits, /*file*/ nullptr, params);
 }
 
 struct llama_model * llama_model_load_from_splits(
@@ -1089,7 +1105,17 @@ struct llama_model * llama_model_load_from_splits(
     for (size_t i = 0; i < n_paths; ++i) {
         splits.push_back(paths[i]);
     }
-    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, splits.front(), splits, params);
+    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, splits.front(), splits, /*file*/ nullptr, params);
+}
+
+struct llama_model * llama_model_load_from_file_ptr(FILE * file, struct llama_model_params params) {
+    if (!file) {
+        LLAMA_LOG_ERROR("%s: file is NULL\n", __func__);
+        return nullptr;
+    }
+    std::string path_model;
+    std::vector<std::string> splits = {};
+    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, path_model, splits, file, params);
 }
 
 void llama_model_save_to_file(const struct llama_model * model, const char * path_model) {