Merge branch 'ggerganov:master' into master

.editorconfig

@@ -26,3 +26,6 @@ indent_size = 2
 
 [examples/llama.swiftui/llama.swiftui.xcodeproj/*]
 indent_style = tab
+
+[examples/cvector-generator/*.txt]
+insert_final_newline = unset

.github/workflows/build.yml

@@ -84,7 +84,7 @@ jobs:
           name: llama-bin-macos-arm64.zip
 
   macOS-latest-cmake-x64:
-    runs-on: macos-latest
+    runs-on: macos-12
 
     steps:
       - name: Clone

CMakeLists.txt

@@ -684,7 +684,8 @@ if (LLAMA_SYCL)
     endif()
 
     set(GGML_HEADERS_SYCL ggml-sycl.h)
-    set(GGML_SOURCES_SYCL ggml-sycl.cpp)
+    file(GLOB GGML_SOURCES_SYCL "ggml-sycl/*.cpp")
+    list(APPEND GGML_SOURCES_SYCL "ggml-sycl.cpp")
 
     if (WIN32)
         set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl sycl7 OpenCL mkl_sycl_blas_dll.lib mkl_intel_ilp64_dll.lib mkl_sequential_dll.lib mkl_core_dll.lib)

Makefile

@@ -38,6 +38,7 @@ BUILD_TARGETS = \
 	llama-tokenize \
 	llama-train-text-from-scratch \
 	llama-vdot \
+	llama-cvector-generator \
 	tests/test-c.o
 
 # Binaries only useful for tests
@@ -922,6 +923,10 @@ llama-eval-callback: examples/eval-callback/eval-callback.cpp ggml.o llama.o $(C
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
+llama-cvector-generator: examples/cvector-generator/cvector-generator.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+
 llama-train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)

common/common.cpp

@@ -1576,6 +1576,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
             return true;
         }
         params.out_file = argv[i];
+        params.cvector_outfile = argv[i];
         return true;
     }
     if (arg == "-ofreq" || arg == "--output-frequency") {
@@ -1610,6 +1611,55 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         params.i_chunk = std::stoi(argv[i]);
         return true;
     }
+    // cvector params
+    if (arg == "--completions-file") {
+        if (++i >= argc) {
+            invalid_param = true;
+            return true;
+        }
+        params.cvector_completions_file = argv[i];
+        return true;
+    }
+    if (arg == "--positive-file") {
+        if (++i >= argc) {
+            invalid_param = true;
+            return true;
+        }
+        params.cvector_positive_file = argv[i];
+        return true;
+    }
+    if (arg == "--negative-file") {
+        if (++i >= argc) {
+            invalid_param = true;
+            return true;
+        }
+        params.cvector_negative_file = argv[i];
+        return true;
+    }
+    if (arg == "--completions") {
+        if (++i >= argc) {
+            invalid_param = true;
+            return true;
+        }
+        params.n_completions = std::stoi(argv[i]);
+        return true;
+    }
+    if (arg == "--pca-batch") {
+        if (++i >= argc) {
+            invalid_param = true;
+            return true;
+        }
+        params.n_pca_batch = std::stoi(argv[i]);
+        return true;
+    }
+    if (arg == "--pca-iter") {
+        if (++i >= argc) {
+            invalid_param = true;
+            return true;
+        }
+        params.n_pca_iterations = std::stoi(argv[i]);
+        return true;
+    }
 #ifndef LOG_DISABLE_LOGS
     // Parse args for logging parameters
     if (log_param_single_parse(argv[i])) {
@@ -1931,6 +1981,16 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "logging",     "       --log-append",           "Don't truncate the old log file." });
 #endif // LOG_DISABLE_LOGS
 
+    options.push_back({ "cvector" });
+    options.push_back({ "cvector",     "-o,    --output FNAME",         "output file (default: '%s')", params.cvector_outfile.c_str() });
+    options.push_back({ "cvector",     "       --positive-file FNAME",  "positive prompts file, one prompt per line (default: '%s')", params.cvector_positive_file.c_str() });
+    options.push_back({ "cvector",     "       --negative-file FNAME",  "negative prompts file, one prompt per line (default: '%s')", params.cvector_negative_file.c_str() });
+    options.push_back({ "cvector",     "       --completions-file FNAME",
+                                                                        "completions file (default: '%s')", params.cvector_completions_file.c_str() });
+    options.push_back({ "cvector",     "       --completions N",        "number of lines of completions file to use (default: %d)", params.n_completions });
+    options.push_back({ "cvector",     "       --batch-pca N",          "batch size used for PCA. Larger batch runs faster, but uses more memory (default: %d)", params.n_pca_batch });
+    options.push_back({ "cvector",     "       --iter-pca N",           "number of iterations used for PCA (default: %d)", params.n_pca_iterations });
+
     printf("usage: %s [options]\n", argv[0]);
 
     for (const auto & o : options) {

common/common.h

@@ -232,6 +232,15 @@ struct gpt_params {
 
     bool process_output = false; // collect data for the output tensor
     bool compute_ppl    = true;  // whether to compute perplexity
+
+    // cvector-generator params
+    int n_completions = 64;
+    int n_pca_batch = 20;
+    int n_pca_iterations = 1000;
+    std::string cvector_outfile          = "control_vector.gguf";
+    std::string cvector_completions_file = "examples/cvector-generator/completions.txt";
+    std::string cvector_positive_file    = "examples/cvector-generator/positive.txt";
+    std::string cvector_negative_file    = "examples/cvector-generator/negative.txt";
 };
 
 void gpt_params_handle_model_default(gpt_params & params);

convert-hf-to-gguf-update.py

@@ -83,6 +83,7 @@ class TOKENIZER_TYPE(IntEnum):
     {"name": "jina-v2-es",     "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-es", },
     {"name": "jina-v2-de",     "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", },
     {"name": "smaug-bpe",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct", },
+    {"name": "poro-chat",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Poro-34B-chat", },
     {"name": "jina-v2-code",   "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", },
 ]
 

convert-hf-to-gguf.py

@@ -477,6 +477,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
         if chkhsh == "c136ed14d01c2745d4f60a9596ae66800e2b61fa45643e72436041855ad4089d":
             # ref: https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct
             res = "smaug-bpe"
+        if chkhsh == "c7ea5862a53e4272c035c8238367063e2b270d51faa48c0f09e9d5b54746c360":
+            # ref: https://huggingface.co/LumiOpen/Poro-34B-chat
+            res = "poro-chat"
         if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a":
             # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code
             res = "jina-v2-code"

examples/CMakeLists.txt

@@ -12,6 +12,7 @@ include_directories(${CMAKE_CURRENT_SOURCE_DIR})
 
 if (EMSCRIPTEN)
 else()
+    add_subdirectory(cvector-generator)
     add_subdirectory(baby-llama)
     add_subdirectory(batched-bench)
     add_subdirectory(batched)

examples/cvector-generator/CMakeLists.txt

@@ -0,0 +1,5 @@
+set(TARGET llama-cvector-generator)
+add_executable(${TARGET} cvector-generator.cpp pca.hpp)
+install(TARGETS ${TARGET} RUNTIME)
+target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
+target_compile_features(${TARGET} PRIVATE cxx_std_11)

examples/cvector-generator/README.md

@@ -0,0 +1,34 @@
+# cvector-generator
+
+This example demonstrates how to generate a control vector using gguf models.
+
+Related PRs:
+- [Add support for control vectors](https://github.com/ggerganov/llama.cpp/pull/5970)
+- (Issue) [Generate control vector using llama.cpp](https://github.com/ggerganov/llama.cpp/issues/6880)
+- [Add cvector-generator example](https://github.com/ggerganov/llama.cpp/pull/7514)
+
+## Examples
+
+```sh
+# CPU only
+./cvector-generator -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf
+
+# With GPU
+./cvector-generator -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf -ngl 99
+
+# With advanced options
+./cvector-generator -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf -ngl 99 --completions 128 --pca-iter 2000 --batch-pca 100
+
+# To see help message
+./cvector-generator -h
+# Then, have a look at "cvector" section
+```
+
+## Tips and tricks
+
+If you have multiple lines per prompt, you can escape the newline character (change it to `\n`). For example:
+
+```
+<|im_start|>system\nAct like a person who is extremely happy.<|im_end|>
+<|im_start|>system\nYou are in a very good mood today<|im_end|>
+```