* BERT model graph construction (build_bert)
* WordPiece tokenizer (llm_tokenize_wpm)
* Add flag for non-causal attention models
* Allow for models that only output embeddings
* Support conversion of BERT models to GGUF
* Based on prior work by @xyzhang626 and @skeskinen
---------
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* vulkan: refactor guess_matmul_pipeline for vendor
Refactor ggml_vk_guess_matmul_pipeline to simplify adding per-vendor
conditionals.
Signed-off-by: Sergio Lopez <slp@redhat.com>
* vulkan: only use M-sized matmul on Apple GPUs
L-sized and S-sized matmuls are broken on Apple GPUs, force using
M-size with this vendor.
Signed-off-by: Sergio Lopez <slp@redhat.com>
---------
Signed-off-by: Sergio Lopez <slp@redhat.com>
* common: use enums for sampler types
* Apply suggestions from code review
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* minor : spaces
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server: allow to specify tokens as strings in logit_bias
* Apply suggestions from code review
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* ggml: aarch64: implement smmla kernel for q8_0_q8_0 quantized gemm
armv8.2-a and above supports MMLA instructions that have higher
throughput than DOT. this commit adds mmla kernel for
q8_0_q8_0 gemm. The feature is enabled if the platform supports
"__ARM_FEATURE_MATMUL_INT8"
On AWS Graviton3 processors this kernel resulted up to 1.5x
improvement for prompt evaluation throughput compared to the
default sdot kernel.
* ggml: aarch64: implement smmla kernel for q4_0_q8_0 quantized gemm
armv8.2-a and above supports MMLA instructions that have higher
throughput than DOT. this commit adds mmla kernel for
q4_0_q8_0 gemm. The feature is enabled if the platform supports
"__ARM_FEATURE_MATMUL_INT8"
On AWS Graviton3 processors this kernel resulted up to 1.5x
improvement for prompt evaluation throughput compared to the
default sdot kernel.
* ggml: aarch64: implement smmla kernel for q4_1_q8_1 quantized gemm
armv8.2-a and above supports MMLA instructions that have higher
throughput than DOT. this commit adds mmla kernel for
q4_1_q8_1 gemm. The feature is enabled if the platform supports
"__ARM_FEATURE_MATMUL_INT8"
On AWS Graviton3 processors this kernel resulted up to 1.5x
improvement for prompt evaluation throughput compared to the
default sdot kernel.
* ggml: update unit tests for the new vec_dot interface
* llama.cpp: add MATMUL_INT8 capability to system_info
A common default for the maximum number of open files is 256, which can
lead to `asyncio.gather(*tasks)` failing with Too many open files.
$ python ggml_vk_generate_shaders.py --glslc=$ANDROID_NDK_PATH/shader-tools/darwin-x86_64/glslc
ggml_vulkan: Generating and compiling shaders to SPIR-V
Traceback (most recent call last):
File "/Users/neuman/Code.noindex/github/llama.cpp/ggml_vk_generate_shaders.py", line 2326, in <module>
asyncio.run(main())
File "/Users/neuman/Code.noindex/miniforge3/lib/python3.10/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/Users/neuman/Code.noindex/miniforge3/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
return future.result()
File "/Users/neuman/Code.noindex/github/llama.cpp/ggml_vk_generate_shaders.py", line 2294, in main
await asyncio.gather(*tasks)
[...snip...]
OSError: [Errno 24] Too many open files
This change sets a reasonable concurrency limit for tasks (and therefore
open files), without significant impact on run time.
* llava: add requirements.txt and update README.md
This commit adds a `requirements.txt` file to the `examples/llava`
directory. This file contains the required Python packages to run the
scripts in the `examples/llava` directory.
The motivation of this to make it easier for users to run the scripts in
`examples/llava`. This will avoid users from having to possibly run into
missing package issues if the packages are not installed on their system.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* llava: fix typo in llava-surgery.py output
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
This commit adds the missing .py extension to the convert-image-encoder-to-gguf
script. It also fixes the paths for the `model` and `mmproj` options in the
example llava-cli command.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* fix bug for norm_rms_eps missing
* to align with the same order as convert.py for model write
* fix: undo HF models permute tensor
* update for flake8 lint
This commit fixes a typo in the README.md file for the llava example
which is causing the formatting to look a little off:
Clone llava-v15-7b`` and clip-vit-large-patch14-336`` locally
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Initial Vulkan multi-gpu implementation
Move most global variables into backend context
* Add names to backend device functions
* Add further missing cleanup code
* Reduce code duplication in tensor split layer assignment
* generalize LLAMA_SPLIT_LAYER for all backends, do not expose device count and memory in llama.h
* Only do device info print in the beginning and initialize one backend for cpu assist
Add missing cleanup code
* Rework backend memory management to make sure devices and buffers get properly allocated and freed
* Rename cpu assist free function
---------
Co-authored-by: slaren <slarengh@gmail.com>
* support minicpm arch.
* fix tab/space typo.
* convert minicpm model via convert-hf-gguf.py
* try to make tokenizer work
* fix bug for quantize minicpm
* fix for flake8 lint
* remove convert-minicpm.py
* fix for editorconfig
* correct minicpm model type (size)
* constants expanded for minicpm
* Minor change of the constant names for minicpm
* include total "num_slots" in default_generation_settings_for_props
* cleanup total_slots return value in /props endpoint
* update /props endpoint docs with total_slots
* remove num_slots from default_generation_settings_for_props
* update /props endpoint section
server : fix deadlock when prompt array contains strings and numbers
server : removed an unnecessary generation when generating multi-prompts
server : removed an unnecessary assert
* Make use of ggml-quants.h possible in C++ code
* One cannot possibly be defining static_assert in a C++ compilation
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* Avoid duplicating function calls when using MIN/MAX macros.
Since these copy "a" and "b" they ask the compiler to evaluate one of them twice. The compiler doesn't have a problem with removing the duplication in something like MAX(0, x + 2), but in some cases we're calling functions, and those calls just happen twice.
By explicitly evaluating at the expression we get smaller and faster code without duplicate calls. See ggml_rope_yarn_corr_dims in Compiler Explorer:
https://godbolt.org/z/Ee4KMrvKh
Code behaves exactly the same.
* Update ggml.c
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
We get slightly better PPL, and we cut quantization time in
nearly half.
The trick is to 1st quantize without forcing points onto the E8-lattice.
We can then use a narrower search range around the block scale that we
got that way.
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* Update server-llm.sh
Add flag --non-interactive that allows run script without asking a permission
* Update scripts/server-llm.sh
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* imatrix: adding --combine and --continue-from
* imatrix: be able to start from a specific chunk
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* Fix Vulkan on Intel ARC
Optimize matmul for Intel ARC
Add Vulkan dequant test
* Add Vulkan debug and validate flags to Make and CMakeLists.txt
* Enable asynchronous transfers in Vulkan backend
* Fix flake8
* Disable Vulkan async backend functions for now
* Also add Vulkan run tests command to Makefile and CMakeLists.txt
* update guide for make installation, memory, gguf model link, rm todo for windows build
* add vs install requirement
* update for gpu device check
* update help of llama-bench
* fix grammer issues
The llama_batch_init allocates memory for a fixed number of tokens.
However, the llama_batch_free only frees memory for the number of
tokens that were added to the batch.
This change-set uses a null terminated array for the batch seq_id, and
frees all the elements until the nullptr is reached. This change-set
also changes the name of the first parameter from `n_tokens` to
`n_tokens_alloc` to more clearly indicate that this value is the number
of tokens allocated to the batch, not the number of tokens in the batch.
* add --no-mmap, show sycl backend
* fix conflict
* fix code format, change print for --no-mmap
* ren no_mmap to mmap, show mmap when not default value in printer
* update guide for mmap
* mv position to reduce model reload
* New Feature:
1. Sum_Rows:
fix cuda kernel overflow
fix block shape error when nrows too big
2. Im2Col:
Support Batch in cuda
Support f32 to f32 both in cpu && cuda
3. DepthWiseConv:
Support by Im2Col && MulMat
4. Pool_2d:
Supoort avg pooling in cuda
5. HardSigmoid:
Imp in cuda
6. HardSwish:
Imp in cuda
* fix tabs instead of spaces
* code clean
* CUDA POOL2D
* ADD POOL2D test case in test-backend-ops.cpp
* code clean
* fix pool2d_kernel
nits
* fix bug in pool2d kernel
* fix avg pooling, count_include_pad
nits
* test-backend-ops : add more pool_2d tests
* cuda : fix warnings and formatting
* ggml : check types in release builds too in pool_2d
* test-backend-ops : remove f16 pool_2d tests
* cuda : more style fixes
* Add assert in ggml_cuda_op_pool2d
* pool2d float padding fallback
* test-backend-ops : add dst_type to im2col
---------
Co-authored-by: slaren <slarengh@gmail.com>
* Fix Vulkan F16 models
* Fix Vulkan context shift crash
* Add Vulkan to common.cpp dump_non_result_info_yaml function
* Fix bug in Vulkan CPY op
* Fix small matrix multiplication errors in AMD GPUs on Windows or with amdvlk
Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>
---------
Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>
* support SYCL backend windows build
* add windows build in CI
* add for win build CI
* correct install oneMKL
* fix install issue
* fix ci
* fix install cmd
* fix install cmd
* fix install cmd
* fix install cmd
* fix install cmd
* fix win build
* fix win build
* fix win build
* restore other CI part
* restore as base
* rm no new line
* fix no new line issue, add -j
* fix grammer issue
* allow to trigger manually, fix format issue
* fix format
* add newline
* fix format
* fix format
* fix format issuse
---------
Co-authored-by: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
github-actions[bot]
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