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* llama : the WPM vocabs use the CLS token as BOS ggml-ci * llama : add comment
* llama_server_response_fields * llama_server_response_fields_fix_issues * params fixes * fix * clarify docs * change to "response_fields" --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* more perfo with llamafile tinyblas on x86_64. - add bf16 suport - change dispache strategie (thanks: ikawrakow/ik_llama.cpp#71 ) - reduce memory bandwidth simple tinyblas dispache and more cache freindly * tinyblas dynamic dispaching * sgemm: add M blocs. * - git 2.47 use short id of len 9. - show-progress is not part of GNU Wget2 * remove not stable test
…ngs endpoints (ggml-org#10967) * add support for base64 * fix base64 test * improve test --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Warning types fixed (observed under MSYS2 GCC 14.2.0): * format '%ld' expects argument of type 'long int', but argument has type 'size_t' * llama.cpp/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp:81:46: warning: missing initializer for member '_STARTUPINFOA::lpDesktop' [-Wmissing-field-initializers] (emitted for all struct field except first)
* multi row k quant shaders! * better row selection * more row choices * readjust row selection * rm_kq=2 by default
…g#10942) * tests: Add im2col perf tests * vulkan: optimize im2col, more elements per thread * vulkan: increase small tile size for NV_coopmat2 * vulkan: change im2col to 512 elements per workgroup
Make the mul_mat_vec shaders support N>1 (as a spec constant, NUM_COLS) where the batch_strides are overloaded to hold the row strides. Put the loads from the B matrix in the innermost loop because it should cache better. Share some code for reducing the result values to memory in mul_mat_vec_base.
…hen building with LLAMA_CURL=ON and GGML_OPENCL=ON (ggml-org#11013) In common/common.cpp: * Convert usage of stat() function call to check if file exists to standard library function std::filesystem::exists (error unable to match to correct function signature) * Additional conditions to check if PATH_MAX is already defined in WIN32 environment (warning it is already defined in MSYS2) In examples/run/run.cpp: * Add io.h header inclusion (error cannot find function _get_osfhandle) * Change initialisers for OVERLAPPED to empty struct (warning about uninitialised members) * Add initialiser for hFile (warning it may be uninitialised) * Add cast for curl_off_t percentage value to long int in generate_progress_prefix function (warning that curl_off_t is long long int) In ggml/src/ggml-opencl/ggml-opencl.cpp: * Initialise certain declared cl_mem variables to nullptr for greater safety (warning about B_d variable possibly used unassigned)
* conflict resolution * move comments after bracket to its own line * DeciLMCausalModel now reads rope_theta from config.json properly
* server : add OAI compat for /v1/completions * add test * add docs * better docs
* server : clean up built-in template detection * fix compilation * add chat template test * fix condition
…g#11027) * Fixes for clang AVX VNNI * enable AVX VNNI and alder lake build for MSVC * Apply suggestions from code review --------- Co-authored-by: slaren <slarengh@gmail.com>
* list llama-swap under tools in README * readme: add llama-swap to Infrastructure
* slot.can_batch_with * lora per request * test: force disable cache prompt * move can_batch_with check * fix condition * add slow test with llama 8b * update docs * move lora change task to queue * Apply suggestions from code review Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * lora_base * remove redundant check --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server/bench: - support openAI streaming standard output with [DONE]\n\n - export k6 raw results in csv - fix too many tcp idle connection in tcp_wait - add metric time to emit first token * server/bench: - fix when prometheus not started - wait for server to be ready before starting bench
* llama : scatter llama.cpp into multiple modules (wip) * llama : control-vector -> adapter * llama : arch * llama : mmap ggml-ci * ci : remove BUILD_SHARED_LIBS=OFF ggml-ci * llama : arch (cont) ggml-ci * llama : chat ggml-ci * llama : model ggml-ci * llama : hparams ggml-ci * llama : adapter ggml-ci * examples : fix ggml-ci * rebase ggml-ci * minor * llama : kv cache ggml-ci * llama : impl ggml-ci * llama : batch ggml-ci * cont ggml-ci * llama : context ggml-ci * minor * llama : context (cont) ggml-ci * llama : model loader ggml-ci * common : update lora ggml-ci * llama : quant ggml-ci * llama : quant (cont) ggml-ci * minor [no ci]
…ls (ggml-org#11053) * Disable KV cache shifting automatically for unsupported models instead of exiting directly Signed-off-by: Molly Sophia <mollysophia379@gmail.com> * Update common/common.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --------- Signed-off-by: Molly Sophia <mollysophia379@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit attempts to improve the log message for the inputs of the splits in the sched_print_assignments function. The motivation for this change is that currently even if there are no inputs a colon is displayed at the end of the line, which can make it a little confusing when reading the output as it could be interpreted as the line below are inputs when they are in fact nodes. With this change the colon will only be printed if there actually are inputs.
…ggml-org#11047) * Added init tensor calling code * Added get_alloc_size forwarding * Cleaned up and improved type/error handling. * fix: remove trailing whitespaces. * Cleanup and use GGML error logging functions. * Handle potentially dangerous edge cases. * Apply suggestions from code review Co-authored-by: Diego Devesa <slarengh@gmail.com> --------- Co-authored-by: Diego Devesa <slarengh@gmail.com>
* convert : extend DEEPSEEK2 model architecture to support DeepseekV3ForCausalLM by adding EXPERT_WEIGHTS_NORM and EXPERT_GATING_FUNC model parameters and FFN_EXP_PROBS_B tensor type * vocab : add DeepSeek V3 pre-tokenizer regexes * unicode : handle ACCENT_MARK and SYMBOL categories in regex * llama : add DeepSeek V3 chat template, handle new model parameters and tensor types --------- Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
Remove duplicated macros, use GGML_LOG_ERROR for errors
* GGUF: C++ refactor, backend support, misc fixes remove ggml_tensor.backend update CODEOWNERS [no ci] remove gguf_get_data from API revise GGUF API data types
* fix: Vulkan shader gen binary path when cross compiling
…gml-org#11117) * Disable GL_KHR_cooperative_matrix Vulkan extension if not available. * Perform Vulkan extensions checks in a more sensible order * Remove unnecessary #ifdef directive
This change upstreams llamafile's cpu matrix multiplication kernels for ppc64le using MMA builtins for quantised int8 datatype. This change results in 10% - 70% improvement in total speed(ie all tokens/total time), across various batch sizes. The patch is tested with Meta-Lllama-3-8B, Mistral-7B, Llama-2-7B-chat-hf models on a IBM POWER10 machine. Signed-off-by: Amrita H S <amritahs@linux.vnet.ibm.com>
* ci : pin dependency to specific version * will this fix ec?
4 tasks
* (wip) support mergekit-extracted lora * support mergekit-extract-lora * use lora->get_scale * correct comment * correct norm name & condition * add some hints
The main motivation for this change is it was not handing ctrl-c/ctrl-d correctly. Modify `read_user_input` to handle EOF, "/bye" command, and empty input cases. Introduce `get_user_input` function to manage user input loop and handle different return cases. Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* Moved scripts dir and fixed pyproject.toml * updated readme * fixed README urls * bump pypi gguf to v0.14.0 * retrigger ci * empty commit - trigger ci
Signed-off-by: hydai <z54981220@gmail.com>
* model: support phimoe * python linter * doc: minor Co-authored-by: ThiloteE <73715071+ThiloteE@users.noreply.github.com> * doc: minor Co-authored-by: ThiloteE <73715071+ThiloteE@users.noreply.github.com> * doc: add phimoe as supported model ggml-ci --------- Co-authored-by: ThiloteE <73715071+ThiloteE@users.noreply.github.com>
* server : add tooltips to settings and themes btn This commit adds tooltips to the settings and themes buttons in the webui. The tooltip will be displayed below the actual buttons when hovered over. The motivation for this change is to clarify the purpose of the themes button. * squash! server : add tooltips to settings and themes btn This commit adds a tooltip to the '...' button when a chat has been started. The tooltip is "Chat options" which think could be a good description as the dropdown contains options to delete or download the current chat. * rm tooltip for 3 dots button --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Since NVIDIA does not release CUDA for in-maintenance versions of Fedora, the process of setting up the CUDA toolkit on Fedora has become quite involved. This guide should help mere mortals install CUDA for development in a Fedora 39 toolbox environment, without affecting the host system.
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…gml-org#16038) Initalizing RESERVED_NAME in is_reserved_name() is not thread safe and leads to corrupted memory when used from multiple threads as can be seen in the asan trace below. This fixes the initialization to make it thread-safe. #0 0x000100abd018 in std::__1::pair<std::__1::__hash_iterator<std::__1::__hash_node<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, void*>*>, bool> std::__1::__hash_table<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::hash<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::equal_to<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>>::__emplace_unique_key_args<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&>(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) __hash_table:1565 #1 0x000100ab0320 in SchemaConverter::visit(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) json-schema-to-grammar.cpp:802 #2 0x000100aafc48 in std::__1::__function::__func<build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&)::$_2, std::__1::allocator<build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&)::$_2>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> (std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>::operator()(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&) function.h:319 #3 0x000100a2c938 in std::__1::__function::__func<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0::operator()(common_grammar_builder const&) const::'lambda'(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&), std::__1::allocator<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0::operator()(common_grammar_builder const&) const::'lambda'(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>, void (nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>::operator()(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&) function.h:319 ggml-org#4 0x000100a139f8 in foreach_function(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&, std::__1::function<void (nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)> const&) chat.cpp:762 ggml-org#5 0x000100a2a7f4 in std::__1::__function::__func<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0, std::__1::allocator<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0>, void (common_grammar_builder const&)>::operator()(common_grammar_builder const&) function.h:319 ggml-org#6 0x000100aa98f4 in build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&) json-schema-to-grammar.cpp:982 ggml-org#7 0x0001009c9314 in common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool) chat.cpp:1110 ggml-org#8 0x0001009b8afc in common_chat_templates_apply_jinja(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:1992 ggml-org#9 0x0001009b533c in common_chat_templates_apply(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:2074 ggml-org#10 0x000100810120 in llamacpp_apply_chat_template+0x724 (predict_oai-98384e17fb94e863:arm64+0x100090120) ... ==45482==Register values: x[0] = 0x00006020004147f8 x[1] = 0x00006080000013c8 x[2] = 0x0000000000000000 x[3] = 0x0000604006289738 x[4] = 0x0000000000000002 x[5] = 0x0000000000000001 x[6] = 0x04034000004b4000 x[7] = 0x0000000000000001 x[8] = 0xbebebebebebebebe x[9] = 0x17d7d7d7d7d7d7d7 x[10] = 0x00000c04000828ff x[11] = 0x0000000000000001 x[12] = 0x000000002018d383 x[13] = 0x0000000000000000 x[14] = 0xfa0000000000fafa x[15] = 0x000010700001ffff x[16] = 0x000000019dc012c0 x[17] = 0x00000001021284f8 x[18] = 0x0000000000000000 x[19] = 0x00000001700acdc0 x[20] = 0x0000000000000002 x[21] = 0x000000002018d384 x[22] = 0x16dd16fd2e731151 x[23] = 0x0000007000020000 x[24] = 0x0000000100c69c08 x[25] = 0x0000000100c69c20 x[26] = 0x00006080000013c7 x[27] = 0x0000000100c69c00 x[28] = 0x00000001700acd60 fp = 0x00000001700aceb0 lr = 0x0000000100abce30 sp = 0x00000001700acd60 AddressSanitizer can not provide additional info. SUMMARY: AddressSanitizer: SEGV __hash_table:1565 in std::__1::pair<std::__1::__hash_iterator<std::__1::__hash_node<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, void*>*>, bool> std::__1::__hash_table<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::hash<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::equal_to<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>>::__emplace_unique_key_args<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&>(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) Thread T5 created by T0 here: #0 0x0001020b99d4 in pthread_create+0x5c (libclang_rt.asan_osx_dynamic.dylib:arm64e+0x359d4) #1 0x000100873910 in std::sys::pal::unix::thread::Thread::new::h77254fdd87a28e05+0x118 (predict_oai-98384e17fb94e863:arm64+0x1000f3910) #2 0x0001007c7a1c in test::run_test::haeb3c2bcd5ed6cf6+0x76c (predict_oai-98384e17fb94e863:arm64+0x100047a1c) #3 0x0001007aedb0 in test::console::run_tests_console::he9d142d704f3a986+0x149c (predict_oai-98384e17fb94e863:arm64+0x10002edb0) ggml-org#4 0x0001007c5758 in test::test_main::hf86a5e20735245b9+0x118 (predict_oai-98384e17fb94e863:arm64+0x100045758) ggml-org#5 0x0001007c5da0 in test::test_main_static::h61ee9c8fd30abca0+0x54 (predict_oai-98384e17fb94e863:arm64+0x100045da0) ... ==45482==ABORTING
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