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2145525a4081d66ff1a87cf43ef809f95a85ac0c
259
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Xuan-Son Nguyen
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d230ddd763 | llama: fix whole source code rebuilt on each new commit (#28278) | ||
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Xuan-Son Nguyen
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2578138397 |
llama: improve TENSOR_READ_LAZY handling (#27837)
* force lazy tensor on cpu if lazy is on * llama: improve TENSOR_READ_LAZY handling |
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Xuan-Son Nguyen
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50f068ffff |
bench: add --tensor-read-lazy (#27881)
* bench: add --tensor-read-lazy * rm the alias * rename to LLAMA_LAZY_MODE_* |
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Xuan-Son Nguyen
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fac889fb38 |
llama: model_loader: add TENSOR_READ_LAZY (#27794)
* llama: model_loader: add TENSOR_GET_ROW_LAZY * add --tensor-read-lazy * rename to TENSOR_READ_LAZY * gen docs * address comments |
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Georgi Gerganov
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4c1a0af40d |
llama : allow virtual igpu devices (#26953)
* llama : allow virtual igpu devices * cont : better comment |
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Daniel BeveniusandGeorgi Gerganov
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680a9ae63d |
cmake : introduce semantic versioning (#26839)
* cmake : introduce semantic versioning (wip)
This commit introduces semantic versioning to llama.cpp.
* squash! cmake : introduce semantic versioning (wip)
* cmake : update test-cmake README notes [no ci]
* include libmtmd in output so show its semversioned
* ci : add make-release workflow
* ci : fix build number check in build-cmake-pkg.yml
* examples : remove trailing whitespace
* ci : abort if upstream ggml version does not exist
* ci : extract step contents into scripts
* ci : add GGML_NATIVE=OFF to ubuntu job
* examples : remove CI build information from test-cmake [no ci]
This commit removes the nightly/release information that I added
previously to keep this focused only on using building and installing
llama.cpp with cmake and being able to quickly verify changes or
troubleshoot issues.
* ci : merge scripts into single script
* remove -dev-build_number support
This commit removes the incremental build number (versioning) support
that I added. This was incorrect and we should only use the semver for
the version. Releases will be tag a nightly build and package
maintainers/managers that build from source can use the tag and it is
therefor important that the correct version is reported. So a
nightly-build will report the semver without the build number. The build
number and commit as availble via cmake and test-cmake has been updated
to include an example of using them:
```console
$ ./build.sh
[test-cmake] version: 0.1.0, build: 10360 (
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153d324bcf |
llama: add default load-mode auto, which avoids mmap on iGPUs (#26081)
* llama: add new default load-mode auto which picks mmap unless a non-Metal iGPU is used * Update ggml/src/ggml-hexagon/ggml-hexagon.cpp Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com> * set mmap_support to false on OpenCL backend * fix order of load modes * use -1 for auto * resolve load mode auto earlier to correctly pick gpu host or cpu memory * add load mode auto to llama-bench * bump virtgpu api version, regenerate docs --------- Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com> Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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fairydreamingandStanisław Szymczyk
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82dbc4f017 |
llama : load MTP tensors only if they are really used (#26296)
* llama : load MTP tensors only if they are really used * llama : skip loading MTP (if not used) in remaining models that support MTP --------- Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com> |
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Aaron Teo
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ad256ded30 |
args: add -lm mlock where it mlocks but doesnt mmap (#26135)
* arg: add `-lm mlock` where it mlocks but doesnt mmap Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: rm unwanted docs changes Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: revert auto-formatting Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * bench: fix automated review point 3 Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: revert the meaning of --mlock to non-mmap'ed mlock Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: update docs Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: remove extra changes from `llama-gen-docs` Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> --------- Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> |
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Aaron Teo
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e6dd0e29a6 |
args: refactor mlock/mmap/directio into load-mode (#20834)
* args: overhaul mmap/mlock/dio into single arg Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: update docs with llama-gen-docs Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * chore: satisfy code quality Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * args: make the `+` sign an actual modifier now Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * chore: general code clean up + comments Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: fix deprecated flags support Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: quick sanity check Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * bench: sync llama-bench argument parsing Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * fix: bugfix variable behaviour + llama-bench lm column size Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: inverse commands should do the opposite instead of doing nothing Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * bench: fix incorrect dash Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * bench: fix missing modifiers for deprecated flags Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * llama: switch back to thread_local Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: switch back to single enum Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: update arg docs Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * chore: fix missing `mlock` from llama_load_mode_from_str + cleanup llama-bench Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * llama: fix mlock not activating Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: add deprecation warning when old and new flags are combined Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * arg: cont add comment for todo in the future Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: sync with upstream Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: re-sync with upstream again Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> --------- Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> |
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Dev-iL
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b4024af6c2 | llama : skip main_gpu validation when no devices are available (#23405) | ||
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Ruben Ortlam
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22cadc1944 | llama: only use one iGPU device by default (#23897) | ||
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Radoslav Gerganov
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1738129bee |
llama : do not skip iGPU when only RPC devices are present (#23868)
After #23007 reclassified integrated CUDA/HIP devices as IGPU, the device selection logic dropped the local iGPU whenever any RPC server was added, because RPC devices made `model->devices` non-empty. On systems where the "iGPU" is the main compute device (e.g. Strix Halo with 128 GiB of unified memory), this caused all tensors to be allocated on the RPC peer alone and model loading to fail. Gate the iGPU inclusion on `gpus.empty()` instead, so RPC peers no longer suppress the local iGPU. closes: #23858 |
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Adrien Gallouët
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3980e04d5a |
llama : add missing call to ggml_backend_load_all() (#22752)
Signed-off-by: Adrien Gallouët <angt@huggingface.co> |
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Adrien Gallouët
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bf76ac77be |
common : only load backends when required (#22290)
* common : only load backends when required Signed-off-by: Adrien Gallouët <angt@huggingface.co> * llama : call ggml_backend_load_all() directly from llama_backend_init() Signed-off-by: Adrien Gallouët <angt@huggingface.co> * Add ggml_backend_load_all() where llama_backend_init() is not used Signed-off-by: Adrien Gallouët <angt@huggingface.co> --------- Signed-off-by: Adrien Gallouët <angt@huggingface.co> |
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Xuan-Son Nguyen
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994118a183 |
model: move load_hparams and load_tensors to per-model definition (#22004)
* git-friendly migration * add build_graph * nits * exclude old code from build * wip * add llm_arch_model_i * prepare downstream functions * nits * nits * wip * wip * add back create_tensor_qkv * fix files missing include * enforce one llm_build per arch * cmake: use glob * missing model params * nits * wip * wip (2) * wip (3) * test-llama-archs is happy * improve switch case * move more stuff into llm_arch_model_i * fix downstream code * nits * nits (2) * fix order * llama_model_base * LLAMA_LOAD_LOCALS * small fix * fix build errors * auto * rm migration script and ifdef |
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Georgi Gerganov
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cfe9838d26 |
fit-params : refactor + add option to output estimated memory per device (#22171)
* fit-params : add option to output estimated memory per device * cont : minor * cont : refactor * cont : move fit params implementation to libcommon * cont : header * cont : headers * cont : codeowners |
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Johannes Gäßler
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fd1c0ec3f0 | llama: fit ctx size for CPU only (#21568) | ||
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Xuan-Son NguyenandGeorgi Gerganov
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fae3a28070 |
ggml : remove ggml-ext.h (#21869)
* ggml: correct placement of ggml-ext.h * ggml : remove ggml-ext.h --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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d6f3030047 |
ggml: backend-agnostic tensor parallelism (experimental) (#19378)
* 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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Johannes GäßlerandSiddhesh2377
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36dafba5c4 |
llama: fix llama-model-saver (#20503)
* llama : add fd-based model loading via llama_model_load_from_fd * llama : address review feedback for fd-based model loading * llama : use FILE pointer instead of fd in public API * llama : use FILE pointer consistently, address review feedback * fixup * fix tensor names * fix llama-model-saver * roundtrip tests * fixup * refactor tests * fix prints * fix model saving * fix CI, disable Chameleon * print seed --------- Co-authored-by: Siddhesh2377 <siddheshsonar2377@gmail.com> |
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Aman GuptaandJohannes Gäßler
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e852eb4901 |
llama-fit: fix regex pattern for gate_up tensors (#20910)
* llama-fit: fix regex pattern for gate_up tensors * Apply suggestions from code review Co-authored-by: Johannes Gäßler <johannesg@5d6.de> --------- Co-authored-by: Johannes Gäßler <johannesg@5d6.de> |
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Johannes Gäßler
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a976ff081b |
llama: end-to-end tests (#19802)
* tests: add end-to-end tests per model architecture * fixup for rebase * fix use-after-free in llama-model-loader.cpp * fix CI * fix WebGPU * fix CI * disable CI for macOS-latest-cmake-arm64 * use expert_weights_scale only if != 0.0f * comments |
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Jakkala Mahesh
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24bc238303 |
llama: fix integer type consistency in split helpers (#18894)
* llama: fix integer type consistency in split helpers * llama: apply minor style fixes * llama: remove trailing whitespace |
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Johannes Gäßler
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e9fd8dcab4 | llama-fit-params: keep explicit --ctx-size 0 (#19070) | ||
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Aaron Teo
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046d5fd44e | llama: use host memory if device reports 0 memory (#18587) | ||
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Johannes Gäßler
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64848deb18 | llama-fit-params: free memory target per device (#18679) | ||
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2038101bd9 |
llama : add use_direct_io flag for model loading (#18166)
* Adding --direct-io flag for model loading * Fixing read_raw() calls * Fixing Windows read_raw_at * Changing type off_t to size_t for windows and Renaming functions * disable direct io when mmap is explicitly enabled * Use read_raw_unsafe when upload_backend is available, not functional on some devices with Vulkan and SYCL * Fallback to std::fread in case O_DIRECT fails due to bad address * Windows: remove const keywords and unused functions * Update src/llama-mmap.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --------- Co-authored-by: jtischbein <jtischbein@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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Johannes Gäßler
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68b4d516c3 | llama-params-fit: fix last devices with low VRAM (#18494) | ||
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d3dce4e0a5 |
sampling : add support for backend sampling (#17004)
* sampling : add support for backend sampling This commit adds support for performing sampling operations on the backend (e.g. GPU) as part of the model computation graph. The motivation for this feature is to enable sampling to be performed directly on the backend as part of the computation graph being executed, allowing for some or all of the sampling to be done on the backend. For example, the backend sampler chain might select/sample a token directly in which case only the sampled token needs to be transferred from device memory to host memory. It is also possible for the backend samplers to perform filtering of the logits, or compute and filter the probability distribution, in which case only the filtered logits or probabilites need to be transferred back to system memory for further processing by CPU samplers. Currently the backend sampling works in a similar manner to how pooling works, it is a function that is called by build_graph and the sampler operations become part of the models computation graph. * llama-cli : add backend sampler configuration * server : add backend sampling options/configuration * webui : add backend sampling options * ggml : add initial cumsum implementation for CUDA * sampling : enable all backend sampler tests This commit enables all exisiting backend sampler tests in the test-backend-sampler. Previously, some tests were disabled because there were missing ggml operation implementations. * graph : do not include llama-model.h * sampling : always expose sampled_ids This commit precomputes and caches the full-vocab token id list in llama_context's constructor, so llama_get_backend_sampled_token_ids_ith always returns a valid pointer. The motivation for this is that this enables both common/sampling.cpp and src/llama-sampling.cpp can simplify their logic. Not all backends samplers that process logits need to set the sampled_tokens_id as they may not change the order of the logits, for example the temperature sampler only scales the logits but does not change their order. Simliar the logit bias sampler only adds bias to specific token ids but does not change the order of the logits. In these cases there will not be a device to host copy of the sampled token ids, and this is the use case where having this precomputed list is useful. * sampling : ensure at most one output token per seq This commit adds a check in the batch allocator to ensure that when backend sampling is enabled, at most one output token is specified per sequence. * CUDA: Optimize argsort for gpu-based token sampling Argsort is used for top-k currently. WE optimize argsort by 2 things: 1. Use `DeviceRadixSort` for single-row/sequence to parallelize it across our SMs 2. Use `DeviceSegmentedSort` for multi-row/sequence as this is the correct entrypoint (the function chooses different execution paths, it contains `DeviceSegmentedRadixSort` as one of the paths and will choose the best one according to heuristics. https://nvidia.github.io/cccl/cub/api/structcub_1_1DeviceSegmentedSort.html#overview Some perf numbers for a RTX PRO 6000: On the kernel level, tested with `GGML_CUDA_DISABLE_GRAPHS=1 ./test-backend-ops -o ARGSORT perf` Before: ``` ARGSORT(type=f32,ne=[65000,16,1,1],order=0): 4130 runs - 359.24 us/run ARGSORT(type=f32,ne=[200000,1,1,1],order=0): 8192 runs - 861.34 us/run ARGSORT(type=f32,ne=[200000,16,1,1],order=0): 1343 runs - 1020.01 us/run ``` After: ``` ARGSORT(type=f32,ne=[65000,16,1,1],order=0): 4130 runs - 312.41 us/run ARGSORT(type=f32,ne=[200000,1,1,1],order=0): 16384 runs - 63.48 us/run ARGSORT(type=f32,ne=[200000,16,1,1],order=0): 1343 runs - 874.36 us/run ``` --- On the model level, tested with `llama-cli -m gpt-oss-20b-mxfp4.gguf -n 200 -p "What is the Capital of Sweden?" -no-cnv -fa 1 --backend-sampling` Before: ``` llama_perf_sampler_print: sampling time = 0.25 ms / 207 runs ( 0.00 ms per token, 824701.20 tokens per second) llama_perf_context_print: load time = 18215.58 ms llama_perf_context_print: prompt eval time = 28.20 ms / 7 tokens ( 4.03 ms per token, 248.19 tokens per second) llama_perf_context_print: eval time = 714.79 ms / 199 runs ( 3.59 ms per token, 278.40 tokens per second) llama_perf_context_print: total time = 857.62 ms / 206 tokens ``` After ``` llama_perf_sampler_print: sampling time = 0.25 ms / 207 runs ( 0.00 ms per token, 828000.00 tokens per second) llama_perf_context_print: load time = 18366.92 ms llama_perf_context_print: prompt eval time = 35.92 ms / 7 tokens ( 5.13 ms per token, 194.87 tokens per second) llama_perf_context_print: eval time = 532.79 ms / 199 runs ( 2.68 ms per token, 373.50 tokens per second) llama_perf_context_print: total time = 683.65 ms / 206 tokens ``` * sampling : remove version from sampler chain This commit removes the version field from the sampler chain and instead used the sampler pointer itself for change detection. * sampling : always populate logits for sampled probs This commit updates common/sampler.cpp set_logits and src/llama-sampling.cpp llama_sampler_sample to always populate the logits field when backend sampled probabilities are available. The motivation for this is that this ensure that CPU sampler always have access to the logits values even when probabilites have been produced by backend samplers. * sampling : simplify backend sampling logic decode This commit tries to simplify the backend sampling logic in llama_context::decode. * squash! sampling : simplify backend sampling logic decode Fix condition to check if backend actually sampled tokens, not just that backend samplers are available. * common : fix regression caused by extra memory allocations during sampling * squash! sampling : simplify backend sampling logic decode The commit fixes a variable shadowing issue in the `llama_context::decode` function which was introduced in a previous refactoring. * squash! common : fix regression caused by extra memory allocations during sampling Apply the same changes to llama-sampling.cpp, llama_sampler_sample as were applied in commit |
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Johannes Gäßler
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f8d561eb87 | llama-fit-params: fix step size for last device (#18415) | ||
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Johannes Gäßler
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a4bf35889e | llama-fit-params: fix overflow check (#18354) | ||
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Johannes Gäßler
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a52dc60ba3 | llama_fit_params: return enum for fail vs. error (#18374) | ||
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Johannes Gäßler
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9045c9afe5 | llama-fit-params: fix Gemma 3 calculation (#18372) | ||
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Johannes Gäßler
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57c1e05643 | llama: offload output layer to GPU first (#18148) | ||
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Johannes Gäßler
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8dcc3662a2 | llama-fit-params: fix memory print (#18136) | ||
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Johannes Gäßler
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d0794e89d9 | llama-fit-params: force disable mlock (#18103) | ||
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Johannes Gäßler
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9dcac6cf9f | llama-fit-params: lower ctx size for multi GPU (#18101) | ||
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Johannes Gäßler
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0e49a7b8b4 | llama-fit-params: fix underflow for dense models (#18095) | ||
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Johannes Gäßler
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ec98e20021 | llama: fix early stop in params_fit if ctx is set (#18070) | ||
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Johannes Gäßler
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b1f3a6e5db |
llama: automatically set parameters not set by the user in such a way that maximizes GPU utilization (#16653)
* llama: automatically fit args to free memory llama-fit-params tool * fix CI * hints for bug reports, ensure no reallocation * fix segfault with Vulkan * add llama-fit-params to CI * fix CI * fix CI * fix CI * minor adjustments * fix assignment of 1 dense layer * fix logger not being reset on model load failure * remove --n-gpu-layer hint on model load failure * fix llama-fit-params verbosity * fix edge case * fix typo [no ci] |
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Xuan-Son NguyenandGeorgi Gerganov
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3e3cb19f64 |
llama-quant: add support for mmproj (#16592)
* llama-quant: add support for mmproj * Update src/llama.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * check prefix instead * small fix --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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Georgi Gerganov
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e38b7c6e9e |
graph : support cacheless embeddings with FA and iSWA (#16528)
* graph : support cacheless embeddings with FA and iSWA * cont : deduplicate mask creation * cont : fix name |
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Diego Devesa
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360d6533db |
ggml-backend : add GGML_BACKEND_DEVICE_TYPE_IGPU device type (#15797)
* ggml-backend : add GGML_BACKEND_DEVICE_TYPE_IGPU device type ggml-backend : add device id to device props llama : only use iGPU devices if there are no GPU devices llama : do not use multiple devices from different backends with the same device id |
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Daniel Bevenius
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86587da03b |
llama : check returned fn ptrs from ggml_backend_reg_get_proc_address (#15893)
This commit adds check for two function pointers returned from ggml_backend_reg_get_proc_address. The motivation for this is that the function pointer could be nullptr if the get proc address function changes in the future. This is also consistent with all the other calls to ggml_backend_reg_get_proc_address in the code base. |
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Johannes Gäßler
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e81b8e4b7f |
llama: use FA + max. GPU layers by default (#15434)
* llama: use max. GPU layers by default, auto -fa * ggml-backend: abort instead of segfault |
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Diego DevesaandGeorgi Gerganov
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6adc3c3ebc |
llama : add thread safety test (#14035)
* llama : add thread safety test * llamafile : remove global state * llama : better LLAMA_SPLIT_MODE_NONE logic when main_gpu < 0 GPU devices are not used --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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Diego Devesa
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5364ae4ba5 | llama : print hint when loading a model when no backends are loaded (#13589) | ||
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Johannes Gäßler
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10d2af0eaa |
llama/ggml: add LLM training support (#10544)
* llama/ggml: add LLM training support more compact progress bar llama_save_model_to_file llama_opt_param_filter ggml_graph_dup force_grads refactor ggml_opt, fix test-opt * remove logits_all * refactor CUDA implementation for ACC * reset graph at beginning of opt period |
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Diego Devesa
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e0e912f49b |
llama : add option to override model tensor buffers (#11397)
* llama : add option to override tensor buffers * ggml : fix possible underflow in ggml_nbytes |