Merge branch 'ggerganov:master' into gguf-model-template

Author: teleprint-me

.devops/llama-cli-intel.Dockerfile

@@ -14,7 +14,9 @@ RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
         echo "GGML_SYCL_F16 is set" && \
         export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
     fi && \
-    cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
+    echo "Building with static libs" && \
+    cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx \
+    ${OPT_SYCL_F16} -DBUILD_SHARED_LIBS=OFF && \
     cmake --build build --config Release --target llama-cli
 
 FROM intel/oneapi-basekit:$ONEAPI_VERSION AS runtime

.devops/llama-server-intel.Dockerfile

@@ -14,6 +14,7 @@ RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
         echo "GGML_SYCL_F16 is set" && \
         export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
     fi && \
+    echo "Building with dynamic libs" && \
     cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
     cmake --build build --config Release --target llama-server
 

.devops/nix/apps.nix

@@ -10,7 +10,6 @@
             "llama-embedding"
             "llama-server"
             "llama-quantize"
-            "llama-train-text-from-scratch"
           ];
           mkApp = name: {
             type = "app";

.devops/tools.sh

@@ -13,8 +13,6 @@ elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
     ./llama-quantize "$@"
 elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
     ./llama-cli "$@"
-elif [[ "$arg1" == '--finetune' || "$arg1" == '-f' ]]; then
-    ./llama-finetune "$@"
 elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
     echo "Converting PTH to GGML..."
     for i in `ls $1/$2/ggml-model-f16.bin*`; do
@@ -36,8 +34,6 @@ else
     echo "              ex: --outtype f16 \"/models/7B/\" "
     echo "  --quantize (-q): Optimize with quantization process ggml"
     echo "              ex: \"/models/7B/ggml-model-f16.bin\" \"/models/7B/ggml-model-q4_0.bin\" 2"
-    echo "  --finetune (-f): Run finetune command to create a lora finetune of the model"
-    echo "              See documentation for finetune for command-line parameters"
     echo "  --all-in-one (-a): Execute --convert & --quantize"
     echo "              ex: \"/models/\" 7B"
     echo "  --server (-s): Run a model on the server"

.github/workflows/build.yml

@@ -860,7 +860,7 @@ jobs:
           mkdir build
           cd build
           cmake .. -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_CUDA=ON -DBUILD_SHARED_LIBS=ON
-          cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS}
+          cmake --build . --config Release -j $((${env:NUMBER_OF_PROCESSORS} - 1))
 
       - name: Determine tag name
         id: tag

CONTRIBUTING.md

@@ -1,12 +1,17 @@
-# Pull requests
+# Pull requests (for contributors)
 
-- Always squash-merge the PR before merging
-- Use the following format for your final commit: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)`
 - Test your changes:
   - Using the commands in the [`tests`](tests) folder. For instance, running the `./tests/test-backend-ops` command tests different backend implementations of the GGML library
   - Execute [the full CI locally on your machine](ci/README.md) before publishing
 - Please rate the complexity of your PR (i.e. `Review Complexity : Low`, `Review Complexity : Medium`, `Review Complexity : High`). This makes it easier for maintainers to triage the PRs.
-  - The PR template has a series of review complexity checkboxes `[ ]` that [you can mark as](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/about-task-lists) `[X]` for your conveience
+  - The PR template has a series of review complexity checkboxes `[ ]` that [you can mark as](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/about-task-lists) `[X]` for your convenience
+- If your PR becomes stale, don't hesitate to ping the maintainers in the comments
+
+# Pull requests (for collaborators)
+
+- Squash-merge PRs
+- Use the following format for the squashed commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)`
+- Optionally, pick a `<module>` from here: https://github.com/ggerganov/llama.cpp/wiki/Modules
 
 # Coding guidelines
 

Makefile

@@ -11,7 +11,6 @@ BUILD_TARGETS = \
 	llama-embedding \
 	llama-eval-callback \
 	llama-export-lora \
-	llama-finetune \
 	llama-gbnf-validator \
 	llama-gguf \
 	llama-gguf-hash \
@@ -37,7 +36,6 @@ BUILD_TARGETS = \
 	llama-simple \
 	llama-speculative \
 	llama-tokenize \
-	llama-train-text-from-scratch \
 	llama-vdot \
 	llama-cvector-generator \
 	tests/test-c.o
@@ -64,13 +62,13 @@ TEST_TARGETS = \
 	tests/test-tokenizer-1-spm
 
 # Legacy build targets that were renamed in #7809, but should still be removed when the project is cleaned
-LEGACY_TARGETS_CLEAN = main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
+LEGACY_TARGETS_CLEAN = main quantize quantize-stats perplexity imatrix embedding vdot q8dot convert-llama2c-to-ggml \
 	simple batched batched-bench save-load-state server gguf gguf-split eval-callback llama-bench libllava.a llava-cli baby-llama \
-	retrieval speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey gritlm
+	retrieval speculative infill tokenize benchmark-matmult parallel export-lora lookahead lookup passkey gritlm
 
 # Legacy build targets that were renamed in #7809, but we want to build binaries that for them that output a deprecation warning if people try to use them.
 #  We don't want to clutter things too much, so we only build replacements for the most commonly used binaries.
-LEGACY_TARGETS_BUILD = main quantize perplexity embedding server finetune
+LEGACY_TARGETS_BUILD = main quantize perplexity embedding server
 
 # Deprecation aliases
 ifdef LLAMA_CUBLAS
@@ -876,6 +874,9 @@ OBJ_GGML += \
 
 OBJ_LLAMA = \
 	src/llama.o \
+	src/llama-vocab.o \
+	src/llama-grammar.o \
+	src/llama-sampling.o \
 	src/unicode.o \
 	src/unicode-data.o
 
@@ -1055,6 +1056,10 @@ src/unicode-data.o: \
 
 src/llama.o: \
 	src/llama.cpp \
+	src/llama-impl.h \
+	src/llama-vocab.h \
+	src/llama-grammar.h \
+	src/llama-sampling.h \
 	src/unicode.h \
 	include/llama.h \
 	ggml/include/ggml-cuda.h \
@@ -1064,6 +1069,29 @@ src/llama.o: \
 	ggml/include/ggml-backend.h
 	$(CXX) $(CXXFLAGS) -c $< -o $@
 
+src/llama-vocab.o: \
+	src/llama-vocab.cpp \
+	src/llama-vocab.h \
+	src/llama-impl.h \
+	include/llama.h
+	$(CXX) $(CXXFLAGS) -c $< -o $@
+
+src/llama-grammar.o: \
+	src/llama-grammar.cpp \
+	src/llama-grammar.h \
+	src/llama-impl.h \
+	src/llama-vocab.h \
+	src/llama-sampling.h \
+	include/llama.h
+	$(CXX) $(CXXFLAGS) -c $< -o $@
+
+src/llama-sampling.o: \
+	src/llama-sampling.cpp \
+	src/llama-sampling.h \
+	src/llama-impl.h \
+	include/llama.h
+	$(CXX) $(CXXFLAGS) -c $< -o $@
+
 $(LIB_LLAMA): \
 	$(OBJ_LLAMA) \
 	$(LIB_GGML)
@@ -1266,11 +1294,6 @@ llama-cvector-generator: examples/cvector-generator/cvector-generator.cpp \
 	$(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 \
-	$(OBJ_ALL)
-	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
-	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-
 llama-convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp \
 	$(OBJ_GGML) $(OBJ_LLAMA)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
@@ -1286,13 +1309,8 @@ llama-baby-llama: examples/baby-llama/baby-llama.cpp \
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
-llama-finetune: examples/finetune/finetune.cpp \
-	$(OBJ_ALL)
-	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
-	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-
 llama-export-lora: examples/export-lora/export-lora.cpp \
-	$(OBJ_GGML) common/log.h
+	$(OBJ_ALL)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
@@ -1439,7 +1457,7 @@ run-benchmark-matmult: llama-benchmark-matmult
 .PHONY: run-benchmark-matmult swift
 
 tests/test-llama-grammar: tests/test-llama-grammar.cpp \
-	$(OBJ_GGML) $(OBJ_COMMON) src/unicode.o src/unicode-data.o
+	$(OBJ_ALL)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
@@ -1548,7 +1566,7 @@ llama-q8dot: pocs/vdot/q8dot.cpp ggml/src/ggml.o \
 # Deprecated binaries that we want to keep around long enough for people to migrate to the new filenames, then these can be removed.
 #
 # Mark legacy binary targets as .PHONY so that they are always checked.
-.PHONY: main quantize perplexity embedding server finetune
+.PHONY: main quantize perplexity embedding server
 
 # NOTE: We currently will always build the deprecation-warning `main` and `server` binaries to help users migrate.
 #  Eventually we will want to remove these target from building all the time.
@@ -1591,13 +1609,3 @@ ifneq (,$(wildcard embedding))
 	@echo "  Remove the 'embedding' binary to remove this warning."
 	@echo "#########"
 endif
-
-finetune: examples/deprecation-warning/deprecation-warning.cpp
-ifneq (,$(wildcard finetune))
-	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
-	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-	@echo "#########"
-	@echo "WARNING: The 'finetune' binary is deprecated. Please use 'llama-finetune' instead."
-	@echo "  Remove the 'finetune' binary to remove this warning."
-	@echo "#########"
-endif

Package.swift

@@ -4,6 +4,9 @@ import PackageDescription
 
 var sources = [
     "src/llama.cpp",
+    "src/llama-vocab.cpp",
+    "src/llama-grammar.cpp",
+    "src/llama-sampling.cpp",
     "src/unicode.cpp",
     "src/unicode-data.cpp",
     "ggml/src/ggml.c",

README.md

@@ -138,6 +138,7 @@ Typically finetunes of the base models below are supported as well.
 
 Unless otherwise noted these projects are open-source with permissive licensing:
 
+- [MindWorkAI/AI-Studio](https://github.com/MindWorkAI/AI-Studio) (FSL-1.1-MIT)
 - [iohub/collama](https://github.com/iohub/coLLaMA)
 - [janhq/jan](https://github.com/janhq/jan) (AGPL)
 - [nat/openplayground](https://github.com/nat/openplayground)
@@ -181,6 +182,9 @@ Unless otherwise noted these projects are open-source with permissive licensing:
 
 - [Paddler](https://github.com/distantmagic/paddler) - Stateful load balancer custom-tailored for llama.cpp
 
+**Games:**
+- [Lucy's Labyrinth](https://github.com/MorganRO8/Lucys_Labyrinth) - A simple maze game where agents controlled by an AI model will try to trick you.
+
 ## Demo
 
 <details>

common/common.cpp

@@ -694,11 +694,6 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         params.lora_adapter.emplace_back(lora_adapter, std::stof(argv[i]));
         return true;
     }
-    if (arg == "--lora-base") {
-        CHECK_ARG
-        params.lora_base = argv[i];
-        return true;
-    }
     if (arg == "--control-vector") {
         CHECK_ARG
         params.control_vectors.push_back({ 1.0f, argv[i], });
@@ -1274,6 +1269,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         CHECK_ARG
         params.out_file = argv[i];
         params.cvector_outfile = argv[i];
+        params.lora_outfile = argv[i];
         return true;
     }
     if (arg == "-ofreq" || arg == "--output-frequency") {
@@ -1583,9 +1579,8 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "*",           "       --override-kv KEY=TYPE:VALUE",
                                                                         "advanced option to override model metadata by key. may be specified multiple times.\n"
                                                                         "types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false" });
-    options.push_back({ "*",           "       --lora FNAME",           "apply LoRA adapter (implies --no-mmap)" });
-    options.push_back({ "*",           "       --lora-scaled FNAME S",  "apply LoRA adapter with user defined scaling S (implies --no-mmap)" });
-    options.push_back({ "*",           "       --lora-base FNAME",      "optional model to use as a base for the layers modified by the LoRA adapter" });
+    options.push_back({ "*",           "       --lora FNAME",           "apply LoRA adapter (can be repeated to use multiple adapters)" });
+    options.push_back({ "*",           "       --lora-scaled FNAME S",  "apply LoRA adapter with user defined scaling S (can be repeated to use multiple adapters)" });
     options.push_back({ "*",           "       --control-vector FNAME", "add a control vector\n"
                                                                         "note: this argument can be repeated to add multiple control vectors" });
     options.push_back({ "*",           "       --control-vector-scaled FNAME SCALE",
@@ -1676,6 +1671,13 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "cvector",     "       --pca-iter N",           "number of iterations used for PCA (default: %d)", params.n_pca_iterations });
     options.push_back({ "cvector",     "       --method {pca,mean}",    "dimensionality reduction method to be used (default: pca)" });
 
+    options.push_back({ "export-lora" });
+    options.push_back({ "export-lora", "-m,    --model",                "model path from which to load base model (default '%s')", params.model.c_str() });
+    options.push_back({ "export-lora", "       --lora FNAME",           "path to LoRA adapter  (can be repeated to use multiple adapters)" });
+    options.push_back({ "export-lora", "       --lora-scaled FNAME S",  "path to LoRA adapter with user defined scaling S  (can be repeated to use multiple adapters)" });
+    options.push_back({ "*",           "-t,    --threads N",            "number of threads to use during computation (default: %d)", params.n_threads });
+    options.push_back({ "export-lora", "-o,    --output FNAME",         "output file (default: '%s')", params.lora_outfile.c_str() });
+
     printf("usage: %s [options]\n", argv[0]);
 
     for (const auto & o : options) {
@@ -2721,7 +2723,7 @@ std::string llama_chat_format_single(const struct llama_model * model,
         const llama_chat_msg & new_msg,
         bool add_ass) {
     std::ostringstream ss;
-    auto fmt_past_msg = llama_chat_apply_template(model, tmpl, past_msg, false);
+    auto fmt_past_msg = past_msg.empty() ? "" : llama_chat_apply_template(model, tmpl, past_msg, false);
     std::vector<llama_chat_msg> chat_new(past_msg);
     // if the past_msg ends with a newline, we must preserve it in the formatted version
     if (add_ass && !fmt_past_msg.empty() && fmt_past_msg.back() == '\n') {
@@ -3166,7 +3168,6 @@ void yaml_dump_non_result_info(FILE * stream, const gpt_params & params, const l
         }
         fprintf(stream, "  - %s: %f\n", std::get<0>(la).c_str(), std::get<1>(la));
     }
-    fprintf(stream, "lora_base: %s\n", params.lora_base.c_str());
     fprintf(stream, "main_gpu: %d # default: 0\n", params.main_gpu);
     fprintf(stream, "min_keep: %d # default: 0 (disabled)\n", sparams.min_keep);
     fprintf(stream, "mirostat: %d # default: 0 (disabled)\n", sparams.mirostat);

common/common.h

@@ -128,7 +128,6 @@ struct gpt_params {
 
     // TODO: avoid tuple, use struct
     std::vector<std::tuple<std::string, float>> lora_adapter; // lora adapter path with user defined scale
-    std::string lora_base  = "";                              // base model path for the lora adapter
 
     std::vector<llama_control_vector_load_info> control_vectors; // control vector with user defined scale
 
@@ -255,6 +254,8 @@ struct gpt_params {
     std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
 
     bool spm_infill = false; // suffix/prefix/middle pattern for infill
+
+    std::string lora_outfile = "ggml-lora-merged-f16.gguf";
 };
 
 void gpt_params_handle_hf_token(gpt_params & params);

common/sampling.cpp

@@ -330,7 +330,7 @@ static llama_token llama_sampling_sample_impl(
         llama_token_data_array single_token_data_array = { &single_token_data, 1, false };
 
         // Apply grammar constraints to the single token
-        llama_sample_grammar(ctx_main, &single_token_data_array, ctx_sampling->grammar);
+        llama_grammar_sample(ctx_sampling->grammar, ctx_main, &single_token_data_array);
 
         // Check if the token is valid according to the grammar by seeing if its logit has been set to -INFINITY
         bool is_valid = single_token_data_array.data[0].logit != -INFINITY;
@@ -421,7 +421,7 @@ static llama_token_data_array llama_sampling_prepare_impl(
 
     // apply grammar checks before sampling logic
     if (apply_grammar && ctx_sampling->grammar != NULL) {
-        llama_sample_grammar(ctx_main, &cur_p, ctx_sampling->grammar);
+        llama_grammar_sample(ctx_sampling->grammar, ctx_main, &cur_p);
     }
 
     return cur_p;
@@ -455,6 +455,6 @@ void llama_sampling_accept(
     ctx_sampling->prev.push_back(id);
 
     if (ctx_sampling->grammar != NULL && apply_grammar) {
-        llama_grammar_accept_token(ctx_main, ctx_sampling->grammar, id);
+        llama_grammar_accept_token(ctx_sampling->grammar, ctx_main, id);
     }
 }