Michael Potter
6bb4908a17
Fix MacOS Sonoma model quantization ( #4052 )
...
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-11-14 12:34:41 -05:00
Eve
c41ea36eaa
cmake : MSVC instruction detection (fixed up #809 ) ( #3923 )
...
* Add detection code for avx
* Only check hardware when option is ON
* Modify per code review sugguestions
* Build locally will detect CPU
* Fixes CMake style to use lowercase like everywhere else
* cleanup
* fix merge
* linux/gcc version for testing
* msvc combines avx2 and fma into /arch:AVX2 so check for both
* cleanup
* msvc only version
* style
* Update FindSIMD.cmake
---------
Co-authored-by: Howard Su <howard0su@gmail.com>
Co-authored-by: Jeremy Dunn <jeremydunn123@gmail.com>
2023-11-05 10:03:09 +02:00
slaren
21958bb393
cmake : disable LLAMA_NATIVE by default ( #3906 )
2023-11-02 14:10:33 +02:00
cebtenzzre
b12fa0d1c1
build : link against build info instead of compiling against it ( #3879 )
...
* cmake : fix build when .git does not exist
* cmake : simplify BUILD_INFO target
* cmake : add missing dependencies on BUILD_INFO
* build : link against build info instead of compiling against it
* zig : make build info a .cpp source instead of a header
Co-authored-by: Matheus C. França <matheus-catarino@hotmail.com>
* cmake : revert change to CMP0115
---------
Co-authored-by: Matheus C. França <matheus-catarino@hotmail.com>
2023-11-02 08:50:16 +02:00
Georgi Gerganov
d69d777c02
ggml : quantization refactoring ( #3833 )
...
* ggml : factor all quantization code in ggml-quants
ggml-ci
* ggml-quants : fix Zig and Swift builds + quantize tool
ggml-ci
* quantize : --pure option for disabling k-quant mixtures
---------
Co-authored-by: cebtenzzre <cebtenzzre@gmail.com>
2023-10-29 18:32:28 +02:00
Georgi Gerganov
2f9ec7e271
cuda : improve text-generation and batched decoding performance ( #3776 )
...
* cuda : prints wip
* cuda : new cublas gemm branch for multi-batch quantized src0
* cuda : add F32 sgemm branch
* cuda : fine-tune >= VOLTA params + use MMQ only for small batches
* cuda : remove duplicated cuBLAS GEMM code
* cuda : add CUDA_USE_TENSOR_CORES and GGML_CUDA_FORCE_MMQ macros
* build : add compile option to force use of MMQ kernels
2023-10-27 17:01:23 +03:00
Georgi Gerganov
2b4ea35e56
cuda : add batched cuBLAS GEMM for faster attention ( #3749 )
...
* cmake : add helper for faster CUDA builds
* batched : add NGL arg
* ggml : skip nops in compute_forward
* cuda : minor indentation
* cuda : batched cuBLAS GEMMs for src0 F16 and src1 F32 (attention ops)
* Apply suggestions from code review
These changes plus:
```c++
#define cublasGemmBatchedEx hipblasGemmBatchedEx
```
are needed to compile with ROCM. I haven't done performance testing, but it seems to work.
I couldn't figure out how to propose a change for lines outside what the pull changed, also this is the first time trying to create a multi-part review so please forgive me if I mess something up.
* cuda : add ROCm / hipBLAS cublasGemmBatchedEx define
* cuda : add cublasGemmStridedBatchedEx for non-broadcasted cases
* cuda : reduce mallocs in cublasGemmBatchedEx branch
* cuda : add TODO for calling cublas from kernel + using mem pool
---------
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
2023-10-24 16:48:37 +03:00
Georgi Gerganov
d28e572c02
cmake : fix add_compile_options on macOS
2023-10-12 14:31:05 +03:00
Georgi Gerganov
db3abcc114
sync : ggml (ggml-backend) ( #3548 )
...
* sync : ggml (ggml-backend)
ggml-ci
* zig : add ggml-backend to the build
2023-10-08 20:19:14 +03:00
Eve
017efe899d
cmake : make LLAMA_NATIVE flag actually use the instructions supported by the processor ( #3273 )
...
* fix LLAMA_NATIVE
* syntax
* alternate implementation
* my eyes must be getting bad...
* set cmake LLAMA_NATIVE=ON by default
* march=native doesn't work for ios/tvos, so disable for those targets. also see what happens if we use it on msvc
* revert 8283237
2023-10-03 19:53:15 +03:00
cebtenzzre
e78f0b0d05
cmake : increase minimum version for add_link_options ( #3444 )
2023-10-02 22:38:43 +03:00
cebtenzzre
9476b01226
cmake : make CUDA flags more similar to the Makefile ( #3420 )
...
* cmake : fix misuse of cxx_flags
* cmake : make CUDA flags more similar to the Makefile
* cmake : fix MSVC build
2023-10-02 16:16:50 +03:00
bandoti
095231dfd3
cmake : fix transient definitions in find pkg ( #3411 )
2023-10-02 12:51:49 +03:00
Cebtenzzre
bc39553c90
build : enable more non-default compiler warnings ( #3200 )
2023-09-28 17:41:44 -04:00
Jag Chadha
527e57cfd8
build : add ACCELERATE_NEW_LAPACK to fix warning on macOS Sonoma ( #3342 )
2023-09-27 18:34:32 +03:00
DAN™
99115f3fa6
cmake : fix build-info.h on MSVC ( #3309 )
2023-09-25 18:45:33 -04:00
Johannes Gäßler
111163e246
CUDA: enable peer access between devices ( #2470 )
2023-09-17 16:37:53 +02:00
Cebtenzzre
3aefaab9e5
check C++ code with -Wmissing-declarations ( #3184 )
2023-09-15 15:38:27 -04:00
Engininja2
7e50d34be6
cmake : fix building shared libs for clang (rocm) on windows ( #3176 )
2023-09-15 15:24:30 +03:00
Andrei
76164fe2e6
cmake : fix llama.h location when built outside of root directory ( #3179 )
2023-09-15 11:07:40 +03:00
Andrei
769266a543
cmake : compile ggml-rocm with -fpic when building shared library ( #3158 )
2023-09-14 20:38:16 +03:00
bandoti
990a5e226a
cmake : add relocatable Llama package ( #2960 )
...
* Keep static libs and headers with install
* Add logic to generate Config package
* Use proper build info
* Add llama as import library
* Prefix target with package name
* Add example project using CMake package
* Update README
* Update README
* Remove trailing whitespace
2023-09-14 20:04:40 +03:00
Tristan Ross
1b6c650d16
cmake : add a compiler flag check for FP16 format ( #3086 )
2023-09-13 16:08:52 +03:00
Johannes Gäßler
0a5eebb45d
CUDA: mul_mat_q RDNA2 tunings ( #2910 )
...
* CUDA: mul_mat_q RDNA2 tunings
* Update ggml-cuda.cu
Co-authored-by: Henri Vasserman <henv@hot.ee>
---------
Co-authored-by: Henri Vasserman <henv@hot.ee>
2023-09-13 11:20:24 +02:00
Eric Sommerlade
b52b29ab9d
arm64 support for windows ( #3007 )
...
Co-authored-by: Cebtenzzre <cebtenzzre@gmail.com>
2023-09-12 21:54:20 -04:00
Jhen-Jie Hong
1b0d09259e
cmake : support build for iOS/tvOS ( #3116 )
...
* cmake : support build for iOS/tvOS
* ci : add iOS/tvOS build into macOS-latest-cmake
* ci : split ios/tvos jobs
2023-09-11 19:49:06 +08:00
Georgi Gerganov
b3e9852e47
sync : ggml (CUDA GLM RoPE + POSIX) ( #3082 )
...
ggml-ci
2023-09-08 17:58:07 +03:00
Przemysław Pawełczyk
cb6c44c5e0
build : do not use _GNU_SOURCE gratuitously ( #2035 )
...
* Do not use _GNU_SOURCE gratuitously.
What is needed to build llama.cpp and examples is availability of
stuff defined in The Open Group Base Specifications Issue 6
(https://pubs.opengroup.org/onlinepubs/009695399/ ) known also as
Single Unix Specification v3 (SUSv3) or POSIX.1-2001 + XSI extensions,
plus some stuff from BSD that is not specified in POSIX.1.
Well, that was true until NUMA support was added recently,
so enable GNU libc extensions for Linux builds to cover that.
Not having feature test macros in source code gives greater flexibility
to those wanting to reuse it in 3rd party app, as they can build it with
FTMs set by Makefile here or other FTMs depending on their needs.
It builds without issues in Alpine (musl libc), Ubuntu (glibc), MSYS2.
* make : enable Darwin extensions for macOS to expose RLIMIT_MEMLOCK
* make : enable BSD extensions for DragonFlyBSD to expose RLIMIT_MEMLOCK
* make : use BSD-specific FTMs to enable alloca on BSDs
* make : fix OpenBSD build by exposing newer POSIX definitions
* cmake : follow recent FTM improvements from Makefile
2023-09-08 15:09:21 +03:00
Kunshang Ji
7f412dab9c
enable CPU HBM ( #2603 )
...
* add cpu hbm support
* add memalign 0 byte check
* Update ggml.c
* Update llama.cpp
* ggml : allow ggml_init with 0 size
* retrigger ci
* fix code style
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-09-08 03:46:56 +02:00
Cebtenzzre
00d62adb79
fix some warnings from gcc and clang-tidy ( #3038 )
...
Co-authored-by: xaedes <xaedes@gmail.com>
2023-09-07 13:22:29 -04:00
Cebtenzzre
9912b9efc8
build : add LLAMA_METAL_NDEBUG flag ( #3033 )
2023-09-05 18:21:10 -04:00
Georgi Gerganov
e36ecdccc8
build : on Mac OS enable Metal by default ( #2901 )
...
* build : on Mac OS enable Metal by default
* make : try to fix build on Linux
* make : move targets back to the top
* make : fix target clean
* llama : enable GPU inference by default with Metal
* llama : fix vocab_only logic when GPU is enabled
* common : better `n_gpu_layers` assignment
* readme : update Metal instructions
* make : fix merge conflict remnants
* gitignore : metal
2023-09-04 22:26:24 +03:00
Cebtenzzre
ef15649972
build : fix most gcc and clang warnings ( #2861 )
...
* fix most gcc and clang warnings
* baby-llama : remove commented opt_params_adam
* fix some MinGW warnings
* fix more MinGW warnings
2023-09-01 16:34:50 +03:00
Cebtenzzre
849408957c
tests : add a C compliance test ( #2848 )
...
* tests : add a C compliance test
* make : build C compliance test by default
* make : fix clean and make sure C test fails on clang
* make : move -Werror=implicit-int to CFLAGS
2023-08-30 09:20:26 +03:00
Georgi Gerganov
3a007648f2
metal : add option to disable debug logs ( close #2764 )
2023-08-29 11:33:46 +03:00
Henri Vasserman
6bbc598a63
ROCm Port ( #1087 )
...
* use hipblas based on cublas
* Update Makefile for the Cuda kernels
* Expand arch list and make it overrideable
* Fix multi GPU on multiple amd architectures with rocblas_initialize() (#5 )
* add hipBLAS to README
* new build arg LLAMA_CUDA_MMQ_Y
* fix half2 decomposition
* Add intrinsics polyfills for AMD
* AMD assembly optimized __dp4a
* Allow overriding CC_TURING
* use "ROCm" instead of "CUDA"
* ignore all build dirs
* Add Dockerfiles
* fix llama-bench
* fix -nommq help for non CUDA/HIP
---------
Co-authored-by: YellowRoseCx <80486540+YellowRoseCx@users.noreply.github.com>
Co-authored-by: ardfork <134447697+ardfork@users.noreply.github.com>
Co-authored-by: funnbot <22226942+funnbot@users.noreply.github.com>
Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
Co-authored-by: jammm <2500920+jammm@users.noreply.github.com>
Co-authored-by: jdecourval <7315817+jdecourval@users.noreply.github.com>
2023-08-25 12:09:42 +03:00
Georgi Gerganov
6381d4e110
gguf : new file format with flexible meta data (beta) ( #2398 )
...
* gguf : first API pass
* gguf : read header + meta data
* gguf : read tensor info
* gguf : initial model loading - not tested
* gguf : add gguf_get_tensor_name()
* gguf : do not support passing existing ggml_context to gguf_init
* gguf : simplify gguf_get_val
* gguf : gguf.c is now part of ggml.c
* gguf : read / write sample models
* gguf : add comments
* refactor : reduce code duplication and better API (#2415 )
* gguf : expose the gguf_type enum through the API for now
* gguf : add array support
* gguf.py : some code style changes
* convert.py : start a new simplified implementation by removing old stuff
* convert.py : remove GGML vocab + other obsolete stuff
* GGUF : write tensor (#2426 )
* WIP: Write tensor
* GGUF : Support writing tensors in Python
* refactor : rm unused import and upd todos
* fix : fix errors upd writing example
* rm example.gguf
* gitignore *.gguf
* undo formatting
* gguf : add gguf_find_key (#2438 )
* gguf.cpp : find key example
* ggml.h : add gguf_find_key
* ggml.c : add gguf_find_key
* gguf : fix writing tensors
* gguf : do not hardcode tensor names to read
* gguf : write sample tensors to read
* gguf : add tokenization constants
* quick and dirty conversion example
* gguf : fix writing gguf arrays
* gguf : write tensors one by one and code reuse
* gguf : fix writing gguf arrays
* gguf : write tensors one by one
* gguf : write tensors one by one
* gguf : write tokenizer data
* gguf : upd gguf conversion script
* Update convert-llama-h5-to-gguf.py
* gguf : handle already encoded string
* ggml.h : get array str and f32
* ggml.c : get arr str and f32
* gguf.py : support any type
* Update convert-llama-h5-to-gguf.py
* gguf : fix set is not subscriptable
* gguf : update convert-llama-h5-to-gguf.py
* constants.py : add layer norm eps
* gguf.py : add layer norm eps and merges
* ggml.h : increase GGML_MAX_NAME to 64
* ggml.c : add gguf_get_arr_n
* Update convert-llama-h5-to-gguf.py
* add gptneox gguf example
* Makefile : add gptneox gguf example
* Update convert-llama-h5-to-gguf.py
* add gptneox gguf example
* Update convert-llama-h5-to-gguf.py
* Update convert-gptneox-h5-to-gguf.py
* Update convert-gptneox-h5-to-gguf.py
* Update convert-llama-h5-to-gguf.py
* gguf : support custom alignment value
* gguf : fix typo in function call
* gguf : mmap tensor data example
* fix : update convert-llama-h5-to-gguf.py
* Update convert-llama-h5-to-gguf.py
* convert-gptneox-h5-to-gguf.py : Special tokens
* gptneox-main.cpp : special tokens
* Update gptneox-main.cpp
* constants.py : special tokens
* gguf.py : accumulate kv and tensor info data + special tokens
* convert-gptneox-h5-to-gguf.py : accumulate kv and ti + special tokens
* gguf : gguf counterpart of llama-util.h
* gguf-util.h : update note
* convert-llama-h5-to-gguf.py : accumulate kv / ti + special tokens
* convert-llama-h5-to-gguf.py : special tokens
* Delete gptneox-common.cpp
* Delete gptneox-common.h
* convert-gptneox-h5-to-gguf.py : gpt2bpe tokenizer
* gptneox-main.cpp : gpt2 bpe tokenizer
* gpt2 bpe tokenizer (handles merges and unicode)
* Makefile : remove gptneox-common
* gguf.py : bytesarray for gpt2bpe tokenizer
* cmpnct_gpt2bpe.hpp : comments
* gguf.py : use custom alignment if present
* gguf : minor stuff
* Update gptneox-main.cpp
* map tensor names
* convert-gptneox-h5-to-gguf.py : map tensor names
* convert-llama-h5-to-gguf.py : map tensor names
* gptneox-main.cpp : map tensor names
* gguf : start implementing libllama in GGUF (WIP)
* gguf : start implementing libllama in GGUF (WIP)
* rm binary commited by mistake
* upd .gitignore
* gguf : calculate n_mult
* gguf : inference with 7B model working (WIP)
* gguf : rm deprecated function
* gguf : start implementing gguf_file_saver (WIP)
* gguf : start implementing gguf_file_saver (WIP)
* gguf : start implementing gguf_file_saver (WIP)
* gguf : add gguf_get_kv_type
* gguf : add gguf_get_kv_type
* gguf : write metadata in gguf_file_saver (WIP)
* gguf : write metadata in gguf_file_saver (WIP)
* gguf : write metadata in gguf_file_saver
* gguf : rm references to old file formats
* gguf : shorter name for member variable
* gguf : rm redundant method
* gguf : get rid of n_mult, read n_ff from file
* Update gguf_tensor_map.py
* Update gptneox-main.cpp
* gguf : rm references to old file magics
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : quantization is working
* gguf : roper closing of file
* gguf.py : no need to convert tensors twice
* convert-gptneox-h5-to-gguf.py : no need to convert tensors twice
* convert-llama-h5-to-gguf.py : no need to convert tensors twice
* convert-gptneox-h5-to-gguf.py : simplify nbytes
* convert-llama-h5-to-gguf.py : simplify nbytes
* gptneox-main.cpp : n_layer --> n_block
* constants.py : n_layer --> n_block
* gguf.py : n_layer --> n_block
* convert-gptneox-h5-to-gguf.py : n_layer --> n_block
* convert-llama-h5-to-gguf.py : n_layer --> n_block
* gptneox-main.cpp : n_layer --> n_block
* Update gguf_tensor_map.py
* convert-gptneox-h5-to-gguf.py : load model in parts to save memory
* convert-llama-h5-to-gguf.py : load model in parts to save memory
* convert : write more metadata for LLaMA
* convert : rm quantization version
* convert-gptneox-h5-to-gguf.py : add file_type key
* gptneox-main.cpp : add file_type key
* fix conflicts
* gguf : add todos and comments
* convert-gptneox-h5-to-gguf.py : tensor name map changes
* Create gguf_namemap.py : tensor name map changes
* Delete gguf_tensor_map.py
* gptneox-main.cpp : tensor name map changes
* convert-llama-h5-to-gguf.py : fixes
* gguf.py : dont add empty strings
* simple : minor style changes
* gguf : use UNIX line ending
* Create convert-llama-7b-pth-to-gguf.py
* llama : sync gguf-llama.cpp with latest llama.cpp (#2608 )
* llama : sync gguf-llama.cpp with latest llama.cpp
* minor : indentation + assert
* llama : refactor gguf_buffer and gguf_ctx_buffer
* llama : minor
* gitignore : add gptneox-main
* llama : tokenizer fixes (#2549 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* convert : update convert-new.py with tokenizer fixes (#2614 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* llama : sync gguf-llama with llama (#2613 )
* llama : sync gguf-llama with llama
* tests : fix build + warnings (test-tokenizer-1 still fails)
* tests : fix wstring_convert
* convert : fix layer names
* llama : sync gguf-llama.cpp
* convert : update HF converter to new tokenizer voodoo magics
* llama : update tokenizer style
* convert-llama-h5-to-gguf.py : add token types
* constants.py : add token types
* gguf.py : add token types
* convert-llama-7b-pth-to-gguf.py : add token types
* gguf-llama.cpp : fix n_head_kv
* convert-llama-h5-to-gguf.py : add 70b gqa support
* gguf.py : add tensor data layout
* convert-llama-h5-to-gguf.py : add tensor data layout
* convert-llama-7b-pth-to-gguf.py : add tensor data layout
* gptneox-main.cpp : add tensor data layout
* convert-llama-h5-to-gguf.py : clarify the reverse permute
* llama : refactor model loading code (#2620 )
* llama : style formatting + remove helper methods
* llama : fix quantization using gguf tool
* llama : simplify gguf_file_saver
* llama : fix method names
* llama : simplify write_header()
* llama : no need to pass full file loader to the file saver
just gguf_ctx
* llama : gguf_file_saver write I32
* llama : refactor tensor names (#2622 )
* gguf: update tensor names searched in quantization
* gguf : define tensor names as constants
* gguf : initial write API (not tested yet)
* gguf : write to file API (not tested)
* gguf : initial write API ready + example
* gguf : fix header write
* gguf : fixes + simplify example + add ggml_nbytes_pad()
* gguf : minor
* llama : replace gguf_file_saver with new gguf write API
* gguf : streaming support when writing files
* gguf : remove oboslete write methods
* gguf : remove obosolete gguf_get_arr_xxx API
* llama : simplify gguf_file_loader
* llama : move hparams and vocab from gguf_file_loader to llama_model_loader
* llama : merge gguf-util.h in llama.cpp
* llama : reorder definitions in .cpp to match .h
* llama : minor simplifications
* llama : refactor llama_model_loader (WIP)
wip : remove ggml_ctx from llama_model_loader
wip : merge gguf_file_loader in llama_model_loader
* llama : fix shape prints
* llama : fix Windows build + fix norm_rms_eps key
* llama : throw error on missing KV paris in model meta data
* llama : improve printing + log meta data
* llama : switch print order of meta data
---------
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
* gguf : deduplicate (#2629 )
* gguf : better type names
* dedup : CPU + Metal is working
* ggml : fix warnings about unused results
* llama.cpp : fix line feed and compiler warning
* llama : fix strncpy warning + note token_to_str does not write null
* llama : restore the original load/save session implementation
Will migrate this to GGUF in the future
* convert-llama-h5-to-gguf.py : support alt ctx param name
* ggml : assert when using ggml_mul with non-F32 src1
* examples : dedup simple
---------
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
* gguf.py : merge all files in gguf.py
* convert-new.py : pick #2427 for HF 70B support
* examples/gguf : no need to keep q option for quantization any more
* llama.cpp : print actual model size
* llama.cpp : use ggml_elements()
* convert-new.py : output gguf (#2635 )
* convert-new.py : output gguf (WIP)
* convert-new.py : add gguf key-value pairs
* llama : add hparams.ctx_train + no longer print ftype
* convert-new.py : minor fixes
* convert-new.py : vocab-only option should work now
* llama : fix tokenizer to use llama_char_to_byte
* tests : add new ggml-vocab-llama.gguf
* convert-new.py : tensor name mapping
* convert-new.py : add map for skipping tensor serialization
* convert-new.py : convert script now works
* gguf.py : pick some of the refactoring from #2644
* convert-new.py : minor fixes
* convert.py : update to support GGUF output
* Revert "ci : disable CI temporary to not waste energy"
This reverts commit 7e82d25f40#2644 )
* gguf : single pass for writing tensors + refactoring writer
* gguf : single pass for writing tensors + refactoring writer
* gguf : single pass for writing tensors + refactoring writer
* gguf : style fixes in simple conversion script
* gguf : refactor gptneox conversion script
* gguf : rename h5 to hf (for HuggingFace)
* gguf : refactor pth to gguf conversion script
* gguf : rm file_type key and method
* gguf.py : fix vertical alignment
* gguf.py : indentation
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* convert-gptneox-hf-to-gguf.py : fixes
* gguf.py : gptneox mapping
* convert-llama-hf-to-gguf.py : fixes
* convert-llama-7b-pth-to-gguf.py : fixes
* ggml.h : reverse GGUF_MAGIC
* gguf.py : reverse GGUF_MAGIC
* test-tokenizer-0.cpp : fix warning
* llama.cpp : print kv general.name
* llama.cpp : get special token kv and linefeed token id
* llama : print number of tensors per type + print arch + style
* tests : update vocab file with new magic
* editorconfig : fix whitespaces
* llama : re-order functions
* llama : remove C++ API + reorganize common source in /common dir
* llama : minor API updates
* llama : avoid hardcoded special tokens
* llama : fix MPI build
ggml-ci
* llama : introduce enum llama_vocab_type + remove hardcoded string constants
* convert-falcon-hf-to-gguf.py : falcon HF --> gguf conversion, not tested
* falcon-main.cpp : falcon inference example
* convert-falcon-hf-to-gguf.py : remove extra kv
* convert-gptneox-hf-to-gguf.py : remove extra kv
* convert-llama-7b-pth-to-gguf.py : remove extra kv
* convert-llama-hf-to-gguf.py : remove extra kv
* gguf.py : fix for falcon 40b
* falcon-main.cpp : fix for falcon 40b
* convert-falcon-hf-to-gguf.py : update ref
* convert-falcon-hf-to-gguf.py : add tensor data layout
* cmpnct_gpt2bpe.hpp : fixes
* falcon-main.cpp : fixes
* gptneox-main.cpp : fixes
* cmpnct_gpt2bpe.hpp : remove non-general stuff
* Update examples/server/README.md
Co-authored-by: slaren <slarengh@gmail.com>
* cmpnct_gpt2bpe.hpp : cleanup
* convert-llama-hf-to-gguf.py : special tokens
* convert-llama-7b-pth-to-gguf.py : special tokens
* convert-permute-debug.py : permute debug print
* convert-permute-debug-master.py : permute debug for master
* convert-permute-debug.py : change permute type of attn_q
* convert.py : 70b model working (change attn_q permute)
* Delete convert-permute-debug-master.py
* Delete convert-permute-debug.py
* convert-llama-hf-to-gguf.py : fix attn_q permute
* gguf.py : fix rope scale kv
* convert-llama-hf-to-gguf.py : rope scale and added tokens
* convert-llama-7b-pth-to-gguf.py : rope scale and added tokens
* llama.cpp : use rope scale kv
* convert-llama-7b-pth-to-gguf.py : rope scale fix
* convert-llama-hf-to-gguf.py : rope scale fix
* py : fix whitespace
* gguf : add Python script to convert GGMLv3 LLaMA models to GGUF (#2682 )
* First pass at converting GGMLv3 LLaMA models to GGUF
* Cleanups, better output during conversion
* Fix vocab space conversion logic
* More vocab conversion fixes
* Add description to converted GGUF files
* Improve help text, expand warning
* Allow specifying name and description for output GGUF
* Allow overriding vocab and hyperparams from original model metadata
* Use correct params override var name
* Fix wrong type size for Q8_K
Better handling of original style metadata
* Set default value for gguf add_tensor raw_shape KW arg
* llama : improve token type support (#2668 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* Improved tokenizer test
But does it work on MacOS?
* Improve token type support
- Added @klosax code to convert.py
- Improved token type support in vocabulary
* Exclude platform dependent tests
* More sentencepiece compatibility by eliminating magic numbers
* Restored accidentally removed comment
* llama : add API for token type
ggml-ci
* tests : use new tokenizer type API (#2692 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* Improved tokenizer test
But does it work on MacOS?
* Improve token type support
- Added @klosax code to convert.py
- Improved token type support in vocabulary
* Exclude platform dependent tests
* More sentencepiece compatibility by eliminating magic numbers
* Restored accidentally removed comment
* Improve commentary
* Use token type API in test-tokenizer-1.cpp
* py : cosmetics
* readme : add notice about new file format
ggml-ci
---------
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: goerch <jhr.walter@t-online.de>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
2023-08-21 23:07:43 +03:00
Kolen Cheung
0919a0f73d
cmake : install ggml-meta.metal if LLAMA_METAL ( #2449 )
2023-08-16 23:09:49 +03:00
Shouzheng Liu
bf83bff674
metal : matrix-matrix multiplication kernel ( #2615 )
...
* metal: matrix-matrix multiplication kernel
This commit removes MPS and uses custom matrix-matrix multiplication
kernels for all quantization types. This commit also adds grouped-query
attention to support llama2 70B.
* metal: fix performance degradation from gqa
Integers are slow on the GPU, and 64-bit divides are extremely slow.
In the context of GQA, we introduce a 64-bit divide that cannot be
optimized out by the compiler, which results in a decrease of ~8% in
inference performance. This commit fixes that issue by calculating a
part of the offset with a 32-bit divide. Naturally, this limits the
size of a single matrix to ~4GB. However, this limitation should
suffice for the near future.
* metal: fix bugs for GQA and perplexity test.
I mixed up ne02 and nb02 in previous commit.
2023-08-16 23:07:04 +03:00
Johannes Gäßler
f64d44a9b9
CUDA: Fixed OpenLLaMA 3b mmq, reduced compile time ( #2590 )
2023-08-13 00:24:45 +02:00
Johannes Gäßler
4f6b60c776
CUDA: Fix models with output size != 32000 ( #2480 )
2023-08-02 16:48:10 +02:00
Johannes Gäßler
b772bba42e
CUDA: fixed cmake F16 option ( #2471 )
2023-07-31 19:52:22 +02:00
Johannes Gäßler
0728c5a8b9
CUDA: mmq CLI option, fixed mmq build issues ( #2453 )
2023-07-31 15:44:35 +02:00
slaren
a113689571
ggml : add graph tensor allocator ( #2411 )
...
* ggml : add graph tensor allocator
* ggml : don't calculate data pointer of unallocated tensors when creating a view with an offset
* ggml : refactor ggml_view_Nd into ggml_view_tensor_offset
2023-07-30 15:58:01 +02:00
Johannes Gäßler
11f3ca06b8
CUDA: Quantized matrix matrix multiplication ( #2160 )
...
* mmq implementation for non k-quants
* q6_K
* q2_K
* q3_k
* q4_K
* vdr
* q5_K
* faster q8_1 loading
* loop unrolling
* add __restrict__
* q2_K sc_high
* GGML_CUDA_MMQ_Y
* Updated Makefile
* Update Makefile
* DMMV_F16 -> F16
* Updated README, CMakeLists
* Fix CMakeLists.txt
* Fix CMakeLists.txt
* Fix multi GPU out-of-bounds
2023-07-29 23:04:44 +02:00
Cebtenzzre
6df1f5940f
make : build with -Wmissing-prototypes ( #2394 )
2023-07-26 21:00:04 +03:00
wzy
78a3d13424
flake : remove intel mkl from flake.nix due to missing files ( #2277 )
...
NixOS's mkl misses some libraries like mkl-sdl.pc. See #2261
Currently NixOS doesn't have intel C compiler (icx, icpx). See https://discourse.nixos.org/t/packaging-intel-math-kernel-libraries-mkl/975
So remove it from flake.nix
Some minor changes:
- Change pkgs.python310 to pkgs.python3 to keep latest
- Add pkgconfig to devShells.default
- Remove installPhase because we have `cmake --install` from #2256
2023-07-21 13:26:34 +03:00
wzy
45a1b07e9b
flake : update flake.nix ( #2270 )
...
When `isx86_32 || isx86_64`, it will use mkl, else openblas
According to
https://discourse.nixos.org/t/rpath-of-binary-contains-a-forbidden-reference-to-build/12200/3 ,
add -DCMAKE_SKIP_BUILD_RPATH=ON
Fix #2261 , Nix doesn't provide mkl-sdl.pc.
When we build with -DBUILD_SHARED_LIBS=ON, -DLLAMA_BLAS_VENDOR=Intel10_lp64
replace mkl-sdl.pc by mkl-dynamic-lp64-iomp.pc
2023-07-19 10:01:55 +03:00
wzy
b1f4290953
cmake : install targets ( #2256 )
...
fix #2252
2023-07-19 10:01:11 +03:00
Howard Su
4e7464ef88
FP16 is supported in CM=6.0 ( #2177 )
...
* FP16 is supported in CM=6.0
* Building PTX code for both of 60 and 61
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2023-07-12 20:18:40 +08:00
