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Nexesenex wants to merge 59 commits intoNexesenex:concedo_exp_llamaster_upfrom
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merge b1565#17
Nexesenex wants to merge 59 commits intoNexesenex:concedo_exp_llamaster_upfrom
ggml-org:master

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jammm and others added 30 commits November 20, 2023 17:02
* Update README.md

* Update README.md

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

---------

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* llama : keep track of used KV cells + better KV cache management

* llama : zero KV cache used upon clear

ggml-ci

* llama : allow exporting a view of the KV cache (#4180)

* Allow exporting a view of the KV cache

* Allow dumping the sequences per cell in common

* Track max contiguous cells value and position as well

* Fix max contiguous empty cells index calculation

Make dump functions deal with lengths or sequences counts > 10 better

* Fix off by one error in dump_kv_cache_view

* Add doc comments for KV cache view functions

Eliminate cell sequence struct; use llama_seq_id directly

Minor cleanups

* common : add -dkvc arg for enabling kv cache dumps

---------

Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
* Fix incorrect format strings and uninitialized variables.

* Address comments

* Add the missing include statement
* Update README.md to use PATH for Windows ROCm

* Update README.md

* Update README.md
llama_token_eos(const struct llama_model *) is currently getting struct llama_context type variable context as a parameter.
* ggml-cuda : support stablelm rope

* remove unused freq_base kernel parameter

* add n_dims parameter to llm_build_k_shift, default to n_rot via overload

* llama : fix llm_build_k_shift args

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add openai-compatible POST /v1/chat/completions API endpoint to server example

* fix code style

* Update server README.md

* Improve server README.md

* Fix server.cpp code style according to review

* server : some style changes

* server : indentation

* server : enable special tokens during tokenization by default

* server : minor code style

* server : change random string generator

* straightforward /v1/models endpoint

---------

Co-authored-by: kir-gadjello <111190790+kir-gadjello@users.noreply.github.com>
Co-authored-by: Tobi Lütke <tobi@Tobis-MacBook-Pro.local>
* reserve space for codepoints

* improvement for the appended 0
* Use mmap in torch load, prefer .bin files when loading

* Revert .bin > .safetensors preference
get the correct n_orig_ctx in metal
* lookahead : init

* lookahead : generate and store n-grams

* lookahead : use loop instead recursion to generate n-grams

* lookahead : initial working implementation

* lookahead : filter repeating n-grams

* lookahead : use deterministic init

* lookahead : add to Makefile

* lookahead : fix a bug in the seq_id of the lookahead tokens

* lookahead : add comments

---------

Co-authored-by: slaren <slarengh@gmail.com>
* copy to llama.cpp as subdir

* attempt enabling metal, fails

* ggml metal compiles!

* Update README.md

* initial conversion to new format, utf8 errors?

* bug fixes, but now has an invalid memory access :(

* added O3, now has insufficient memory access

* begin sync with master

* update to match latest code, new errors

* fixed it!

* fix for loop conditionals, increase result size

* fix current workflow errors

* attempt a llama.swiftui workflow

* Update .github/workflows/build.yml

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
…g.cmake (#3970)

* Split CPP generation from build-info query

* Remove blank lines

* Add BUILD_SHARED_LIBS option
…l offload checks in llama.cpp (#4240)

* ggml : use blas even if src0 is not F32

* llama : use n_threads_batch only when n_tokens >= 32

ggml-ci

* llama : revert n_threads_batch logic

ggml-ci
ensan-hcl and others added 23 commits November 30, 2023 23:45
* fix: readme

* chore: resolve comments

* chore: resolve comments
* main : Call llama_log_set to use LOG_TEE

* tabs to spaces
* ShareGPT4 compatibility (vision encoder only loading)

Load only a CLIP vision encoder (as supplied by ShareGPT finetunes)
Corrects the argument parsing for --img_mean and --img_std (which were previously not parsed but attempted to access)
Defines defaults for img_mean and img_std which are equal to the llava 1.5 CLIP encoder, so you do not have to provide them

* Update convert-image-encoder-to-gguf.py
* cmake : fix joining of REAL_GIT_DIR

* fix includes with help from include-what-you-use

* make : remove unneeded deps and add test-rope target

* fix C includes in C++ source files

* Revert "fix includes with help from include-what-you-use"

This reverts commit 635e9fa.
Co-authored-by: Will Findley <findley@gmail.com>
* * add multiprompt support

* * cleanup

* * more cleanup

* * remove atomicity of id_gen, and change lock_guard to unique_lock on completion requests

* * remove all references to mutex_multitasks

* Update examples/server/server.cpp

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* Update examples/server/server.cpp

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* Update examples/server/server.cpp

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* Update examples/server/server.cpp

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* * change to set

---------

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* * add --log-disable to disable logging to file in the server example

* * typo fix
* metal : implement soft_max_ext

* cuda : implement soft_max_ext

* ggml : implement soft_max_ext (CPU)

* batched-bench : print threads

ggml-ci

* metal : simplify soft_max encoding

ggml-ci

* cuda : use 512 threads for soft_max instead of 32

* ggml : update soft max cpu

* cuda : do warp-based block reduce

* cuda : increase max block size to 1024

* cuda : fix warp reduction initialization of shared mem

* metal : warp-based reduction for soft max kernel

* metal : warp-based reduce for rms_norm

* metal : simplify soft max kernel

ggml-ci

* alloc : fix build with debug
This commit adds a requirements file for the convert-hf-to-gguf.py
script, and also add the torch and transformers packages to it.

The motivation for this is that currently running convert-hf-to-gguf.py
will produce the following error:
```console
$ python3 -m venv venv
$ source venv/bin/activate
(venv) $ pip install -r requirements.txt
Collecting numpy==1.24.4
Collecting sentencepiece==0.1.98
Collecting gguf>=0.1.0
Installing collected packages: sentencepiece, numpy, gguf
Successfully installed gguf-0.5.1 numpy-1.24.4 sentencepiece-0.1.98

(venv) $ python convert-hf-to-gguf.py --help
Traceback (most recent call last):
  File "llama.cpp/convert-hf-to-gguf.py", line 16, in <module>
    import torch
ModuleNotFoundError: No module named 'torch'
```
With this commit, and using requirements-hf-to-gguf.txt instead of
requirements.txt, the script can be run and shows the help output.

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
happens with multi-threaded quantization of Qwen-72B

ggml-ci
* enable qwen to llama.cpp

* llama : do not GPU split bias tensors

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Support attention_bias on LLaMA architecture

QKVO bias, should fix InternLM (#3133) and works for LLaMAfied Qwen models (#3743 (comment)).

* check existence of qkvo bias while loading llama models

Tested on LLaMA2, CUDA and CPU.

* Update llama.cpp
* Fix token_to_piece implementation in Swift

* Fix errors
* llama : pad KV cache size to 32

* metal : try to improve batched decoding
* ggml : fix soft max out-of-bounds access

ggml-ci

* ggml : reuse ggml_get_n_tasks() in ggml_graph_plan()

ggml-ci
@Nexesenex Nexesenex deleted the branch Nexesenex:concedo_exp_llamaster_up December 4, 2023 00:43
@Nexesenex Nexesenex closed this Dec 4, 2023
Nexesenex pushed a commit that referenced this pull request Dec 22, 2024
* Merge mainline

* Fix after merge

* Remove CI check

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Nexesenex pushed a commit that referenced this pull request Jul 1, 2025
Nexesenex pushed a commit that referenced this pull request Feb 18, 2026
* Basic JIT compilation for mul_mat, get_rows, and scale (#17)

* scale jit working

* preliminary working jit for getrows and mulmat, needs refining

* simplified mul_mat preprocessing switch statement

* get_rows fixes, mul_mat refinement

* formatted + last edits

* removed some extraneous prints

* fixed get_rows, fixed workgroup dispatch in mul_mat. no gibberish

* small fix

* some changes, working

* get_rows and mul_mat jit fixed and working

* Update formatting

* formatting

* Add header

---------

Co-authored-by: Neha Abbas <nehaabbas@ReeseLevines-MacBook-Pro.local>
Co-authored-by: Reese Levine <reeselevine1@gmail.com>

* Start work on all-encompassing shader library

* refactor argmax, set_rows

* Refactor all but flashattention, mat mul

* flashattention and matrix multiplication moved to new format

* clean up preprocessing

* Formatting

* remove duplicate constants

* Split large shaders into multiple static strings

---------

Co-authored-by: neha-ha <137219201+neha-ha@users.noreply.github.com>
Nexesenex pushed a commit that referenced this pull request Apr 4, 2026
…better shader parameter handling (ggml-org#20173)

* K quant speedup (#20)

* Basic JIT compilation for mul_mat, get_rows, and scale (#17)

* scale jit working

* preliminary working jit for getrows and mulmat, needs refining

* simplified mul_mat preprocessing switch statement

* get_rows fixes, mul_mat refinement

* formatted + last edits

* removed some extraneous prints

* fixed get_rows, fixed workgroup dispatch in mul_mat. no gibberish

* small fix

* some changes, working

* get_rows and mul_mat jit fixed and working

* Update formatting

* formatting

* Add header

---------

Co-authored-by: Neha Abbas <nehaabbas@ReeseLevines-MacBook-Pro.local>
Co-authored-by: Reese Levine <reeselevine1@gmail.com>

* Start work on all-encompassing shader library

* refactor argmax, set_rows

* Refactor all but flashattention, mat mul

* no gibberish, all k quants added, merged

* vec memory fix

* q6_k matching metal on my machine, tests passing

* Set tile size for q6_k separately

* Separate out fast shaders

---------

Co-authored-by: neha-ha <137219201+neha-ha@users.noreply.github.com>

* Move towards writeBuffer for params

* Move away from multiple buffers for set_rows errors, remove host buffer for parameter buffers, minor cleanups

* Remove extra file

* Formatting

---------

Co-authored-by: neha-ha <137219201+neha-ha@users.noreply.github.com>
Nexesenex pushed a commit that referenced this pull request Apr 16, 2026
)

* ggml: backend-agnostic tensor parallelism

* support for GPT-OSS, Qwen 3 MoE

* partial Vulkan fix

* add support for 4/8 GPUs

* unconditional peer access

* re-use buffers + ggml contexts

* fix output pattern

* NCCL support

* GGML: HIP: add RCCL support

* Remove shfl and AllReduce from backend interface

* move allocation workaround out of ggml-alloc.c

* 2d tensor set/get support

* Fix the seg fault without NCCL

* Apply suggestion from JohannesGaessler

* support for tensor dims % n_devs != 0

* fix view_offs scaling

* arbitrary num. of GPUs/tensor split

* fix compilation

* better granularity estimate

* Support device-specific host buffer types if all underlying backends expose the same type. This allows using pinned memory instead of pageable memory for CUDA.

Fix compilation errors.

* partial Qwen 3 Next support

* Fix qwen3 30b (#8)

* Fix crash with Qwen-30B-A3B Q4_0

Qwen-30B-A3B Q4_0 has an intermediate dimension of 768. Using a granularity of 256 forces an uneven split between GPUs, which is not supported by the current implementation.

* Decide block size based on tensor quantization type

* Fix crashes due to KV cache serialization (#9)

KV cache serialization requires non-zero offsets on the tensor. Add support in the meta backend to set/get a tensor with a non-zero offset.

* metal : fix build (#7)

* static memory allocations, fix usage count

* fix tensor granularity

* more even memory distribution

* use BF16 for allreduce

* rebase fixup

* better error message for unsupported architectures

* Fix device mismatch during scatter of allReduce. (#11)

There is a mismatch between the dst buffer device and the backend device, causing the use of sync copies

* Enable the previous allreduce implementation. It is better in both perf and stability (#12)

* delay AllReduce for Moe for less I/O

* build : clean-up compile warnings

* backend : move most of the meta backend API to ggml-backend-impl.h

* cont : hide unused public API in the implementation

* llama : use llama_device + remove ggml_backend_dev_is_meta()

* ggml-backend : remove unused alloc include

* minor : remove regex include

* ggml : introduce ggml-ext.h for staging new APIs

* rebase fixup

* fix tests

* llama : more robust logic for determining Meta devices (#16)

* llama : more robust logic for determining Meta devices

* cont : fix devs size check

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* cont : fix log type

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* disable roundtrip for meta backend

* fix arch selection

* Qwen 3.5 support

* fix Gemma 4 MoE

* fix OpenVino, SYCL

* fix test-llama-archs for CPU-only builds

* Fix Qwen 3.5 MoE

* disable meta backend tests for WebGPU

* tests : filter CPU-based devices from the Meta backend tests (#17)

* meta : formatting, naming, indentation (#18)

* formatting : llama-model.cpp

* formatting : ggml-ext.h

* formatting : ggml-backend-meta.cpp

* meta : add TODO

* add documentation

* better error messages

* fix GPT-OSS

---------

Co-authored-by: Carl Philipp Klemm <carl@uvos.xyz>
Co-authored-by: Gaurav Garg <gaugarg@nvidia.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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