* ggml : add IQ2 to test-backend-ops + refactoring
ggml-ci
* cuda : update supports_op for IQ2
ggml-ci
* ci : enable LLAMA_CUBLAS=1 for CUDA nodes
ggml-ci
* cuda : fix out-of-bounds-access in `mul_mat_vec_q`
ggml-ci
* tests : avoid creating RNGs for each Q tensor
ggml-ci
* tests : avoid creating RNGs for each tensor
ggml-ci
* backend : add eval callback
ggml-ci
* backend : group nodes in a single compute when user don't need them
* backend : clean-up the implementation
ggml-ci
* simple : do not perform tensor data copy if not needed
* simple : fix
* imatrix : offload to GPU support
* imatrix : fix ggml_mul_mat_id hanlding
ggml-ci
* ci : add imatrix test
ggml-ci
* ci : rearrange output
ggml-ci
* backend : add eval callback
ggml-ci
* backend : group nodes in a single compute when user don't need them
* backend : clean-up the implementation
ggml-ci
* simple : do not perform tensor data copy if not needed
* simple : fix
* simple : no need for ggml_is_contiguous + fix bool parse
* llama : fix callback placement in llama_context_params
* backend : avoid double-ask callback calls
* simple : restore examples, imatrix will serve as a demo
This commit adds the name of the training data file to the log message
printed when the training data is tokenized.
The motivation for this change is that it can be useful to show which
file is being tokenized when running the finetune example.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Introduce starter project for Android
Based on examples/llama.swiftui.
* Add github workflow
* Set NDK version
* Only build arm64-v8a in CI
* Sync bench code
* Rename CI prop to skip-armeabi-v7a
* Remove unused tests
* metal: Log `recommendedMaxWorkingSetSize` on iOS 16+
* Only log on iOS and macOS, ignoring tvOS and other platforms
* Check for Xcode version before using recommendedMaxWorkingSetSize
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This change makes it possible to build ggml-cuda.cu and ggml-metal.m as
independent dynamic shared objects, that may be conditionally linked at
runtime in a multiplatform binary. It introduces a GGML_CALL annotation
that documents which functions have a cyclic call relationship, between
the application code and GPU modules.
This change does nothing, unless the build defines -DGGML_MULTIPLATFORM
which causes back-references and function pointers to conform to MS ABI
which is supported by NVCC, ROCm, XCode, GCC and Clang across platforms
This commit replaces the magic number LLAMA_FILE_MAGIC_LORA used in
finetune.cpp with LLAMA_FILE_MAGIC_GGLA defined in llama.h.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Fix ffn_down quantization mix for MoE models
In #4872 I did not consider the part where every third
tensor is quantized with more bits. Fir MoE this leads to tensors
of the same layer being quantized with different number of bits,
which is not considered as a possibility in the inference implementation
(it is assumed all experts use the same quantization).
* Fix the fix
* Review suggestion
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Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
