- 06 Nov, 2025 1 commit
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Daniel Hiltgen authored
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- 13 Oct, 2025 1 commit
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Gabe Goodhart authored
Llama cpp bump (df1b612): granite docling / mamba2 optimizations / multimodal encoding fixes (#12552) * feat: Bump llama.cpp to df1b612 Branch: LlamaCPPBump-GraniteDocling Signed-off-by:
Gabe Goodhart <ghart@us.ibm.com> * fix(mtmd): Correctly encode text chunks during mtmd tokenization There can be text chunks that appear interspersed with the image embeddings that contain template delimiter tokens for some models. These need to be correctly translated to text tokens. Branch: LlamaCPPBump-GraniteDocling Signed-off-by:
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- 02 Oct, 2025 1 commit
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Daniel Hiltgen authored
Notable EOLs with this change: - MacOS v12 and v13 are no longer supported (v14+ required) - AMD gfx900 and gfx906 are no longer supported
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- 30 Sep, 2025 1 commit
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Jesse Gross authored
For each memory allocation we report the size of the (attempted) allocation and whether it succeeded or failed. The latter status reporting proved to be not that useful in practice as systems such as Windows can automatically overflow from VRAM into RAM, resultings in successful allocations even when there isn't enough memory where we wanted. As a result, this information is only used for debug logging, which isn't worthwhile enough for the amount of code. It also isn't fully accurate, as multiple allocations may result in partial failures.
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- 14 Aug, 2025 1 commit
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Michael Yang authored
* TEMPORARY: Update the llama.cpp upstream to my fork's Granite Four branch This will be redone once my branch is merged upstream in llama.cpp * feat: Update all patches There are a number that are no longer needed at all: - 0003-embeddings: Embeddings entirely overhauled on master - 0008-ensure-KV-cache-is-fully-defragmented: KV caching entirely overhauled on master - 0019-metal-add-mean-kernel-14267: Merged upstream - 0020-CUDA-add-mean-operation-14313: Merged upstream * feat: Sync llama.cpp and ggml * fix: Update rsync-filter for all moved/new/removed files * fix: Add files missing from sync * fix: Update ggml rsync-filter for new ggml-cpu/arch subdirs * fix: Add ggml files missing from sync * fix: Narrow llama.cpp rsync-filter to not include mtmd main tool cpp files * fix: Remove mtmd main cpp files * fix: Add missing include in sampling_ext.cpp * fix: Update llama.go to use mtmd instead of clip/llava * fix: Add patch for mtmd_input_text * chore: Ignore *.patched in the patch directory * fix: Fix support for arch-specific ggml-cpu source files with new arrangement In https://github.com/ggml-org/llama.cpp/pull/13892, all arch-specific implementations were split out into a nested tree structure under ggml-cpu/arch. This conflicts with standard CGO layout where all arch-specific source files are expected to live in the same directory as the parent go module and use suffixes based on GOOS and GOARCH. As such, there were really two options for getting this to work: 1. Add a patch on top of the GGML sync to rearrange the files to match the GO layout convention 2. Use CGO directives to conditionally include the nested source files in the compilation units This commit does (2) in order to minimize the set of changes needed on top of the upstream file layout. To get this to work, there are two key things needed: 1. In cpu.go, #cgo directives are added to explicitly set __${GOARCH}__ in the preprocessor directives 2. In arch-impls.c|cpp, use an #ifdef | #elif defined | #endif chain to explicitly include the .c|.cpp files for the given architecture from the nested directory * fix: Use mtmd_helper to correctly load the bitmap for the image * fix: Apply patch for mtmd_text_input * fix: Add missing stb to llama.cpp rsync-filter * fix: Add sync'ed stb vendored header * fix: Use c++17 and include vendor for go wrapper modules * fix: Update patch 0015 for upstream implementation of uuid * feat: Bump to the latest tip of the branch * fix: Update patches for bump * feat: Bump back to the cenral repo and point at the latest master This includes granite 4 and a number of other model architectures! * fix: Revert changes to ggml export GPU UUID patch * fix: Add patch for GGML_VERSION and GGML_COMMIT constants * feat: Sync all patched code * build: Include cmake/common.cmake in ggml sync * build: Add top-level include for GNUINstallDirs in CMakeLists.txt This is used to populate CMAKE_INSTALL_BINDIR * fix: Add a patch to avoid power throttling API on non-msvc windows builds * fix: Sync patch changes for ggml-cpu.c * feat: Bump llama.cpp to 4a4f42 This picks up support for Kimi K2 and PLaMO-2 * feat: Sync llama.cpp * fix: Handle multi-chunk image encodings from mtmd * fix: Re-number patches after merge with `main` * feat: Bump to 41e78c in the makefile * fix: Fix Solar and argsort/copy patches after bump * fix: Remove Gemma3n CUDA Graphs patch It was implemented upstream: https://github.com/ggml-org/llama.cpp/pull/14741 * feat: Sync llama.cpp / ggml after latest bump * build: Remove unnecessary CFLAGS definitions in cpu.go * fix: Remove unnecessary additions in the rsync-filter * fix: Remove unused vendored code for chat template parsing * Revert "fix: Remove Gemma3n CUDA Graphs patch" This reverts commit d724caced3ce21f08924d4b7801f94ce6638f6ea. * fix: Update 0020 CUDA Graphs for gemma3n to keep both llama.cpp and ollama fixes https://github.com/ollama/ollama/pull/11195#issuecomment-3137312394 * fix: Sync ggml-cuda.cu after keeping both style cuda graph fixes for gemma3n * unwind mxfp4 patch Prepare to bump ggml with their impl for mxfp4 * bump * fix windows build error * Convert tensors at load time Repack the mxfp4 tensors as ggmls kernels expect them to be. * convert mlp bf16 to f32 * buffer the conversion better * reshape earlier * openai swiglu * add ids * split qkv, gate_up * fix nested alt tags * fast attention * remove debug messages * fix lint * remove redundant test * remap values only if source/target are different * add back i32->i32 copy * refactor cpu quants * clean up vendor * update patch instructions * clean up patches * remove webgpu * update mem * also handle gpt-oss * revert convert changes --------- Signed-off-by:Daniel Hiltgen <daniel@ollama.com>
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- 22 May, 2025 1 commit
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Jesse Gross authored
GGML has a function to report the allocated size of a backend buffer. However, this returns 0 if we tried to allocate a buffer and it failed. For memory management purposes, it's important to know how much we were trying to allocate. This extends the API to report attempted sizes for all buffers and whether it succeeeded.
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