Sync master with upstream release b6314 #221
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* add fused group_norm/norm, mul, add * fix spacing * revert rms_norm logic * fix trailing whitespace
This commit updates the bash completion script to include the -m short option for the --model argument. The motivation for this is that currently tab completion only works the full --model option, and it is nice to have it work for the short option as well.
* ggml-cpu : add basic RVV support for vector f32 ops * ggml-cpu : add RVV support for f32 softmax
…15561) * CANN(flash-attn): refactor mask handling and improve performance 1. Refactored the mask computation in Flash Attention, unified the logic without separating prefill and decode. 2. Optimized performance in non-alibi scenarios by reducing one repeat operation. 3. Updated operator management to explicitly mark unsupported cases on 310P devices and when dim is not divisible by 16. Signed-off-by: noemotiovon <[email protected]> * [CANN]: fix review Signed-off-by: noemotiovon <[email protected]> * [CANN]: Optimization FA BNSD to BSND Signed-off-by: noemotiovon <[email protected]> --------- Signed-off-by: noemotiovon <[email protected]>
…rg#15622) Prior to this change, we faced undefined cublasLt references when attempting to compile 'llama-cli' with GGML_STATIC=ON on Linux. We add linking with CUDA::cublasLt_static when CUDA version is greater than 10.1.
This commit adds a new target to the Makefile for converting models that are multimodal. This target will convert the original model and in addition also create the mmproj GGUF model. The motivation for this change is that for models that are multimodal, for example those that contain a vision encoders, we will often want to upload both the quantized model and the vision encoder model to HuggingFace. Example usage: ```console $ make causal-convert-mm-model MODEL_PATH=~/work/ai/models/gemma-3-4b-it-qat-q4_0-unquantized/ ... The environment variable CONVERTED_MODEL can be set to this path using: export CONVERTED_MODEL=/home/danbev/work/ai/llama.cpp/models/gemma-3-4b-it-qat-q4_0-unquantized.gguf The mmproj model was created in /home/danbev/work/ai/llama.cpp/models/mmproj-gemma-3-4b-it-qat-q4_0-unquantized.gguf ``` The converted original model can then be quantized, and after that both the quantized model and the mmproj file can then be uploaded to HuggingFace. Refs: https://huggingface.co/ggml-org/gemma-3-4b-it-qat-GGUF/tree/main
…15604) * Change to warn instead of debug, to explain reason for stopping. * Update tools/main/main.cpp Fix printing --2 Co-authored-by: Georgi Gerganov <[email protected]> --------- Co-authored-by: Georgi Gerganov <[email protected]>
* gguf-py: implement byteswapping for Q4_0 This is needed to byteswap Mistral model. Also restore original shapes after byteswapping tensors. It is not needed at the moment, but do it in case they'd be used in future. * Rework byteswapping code in gguf-py Move out details from byteswapping tensor blocks code
* initial jina-embeddings-v3 support * initial jina-embeddings-v3 support * initial jina-embeddings-v3 support * fix vocab parsing with only tokenizer.json * set mask token lstrip attribute * additional unk_token_id fallback just in case [no ci] * revert vocab_size() change [no ci] * merge tensor loading into general bert * rope * add lora embedding and loading (non-functional) * export separate lora ggufs instead * add adapter metadata api * use std::string * convert_hf_to_lora compatibility * fix assert * apply suggestions from review * apply suggestion from review
Signed-off-by: Aaron Teo <[email protected]>
* CUDA: add conv2d * CUDA: conv2d - correct formatting and added const
… printed values (ggml-org#15637) This makes it much easier to compare between llama.cpp and transformers! https://github.com/ggml-org/llama.cpp/issues/nemotron-nano-15409 Branch: gabe-l-hart/nvidia-nemotron-nano-15409 Signed-off-by: Gabe Goodhart <[email protected]>
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Aug 29, 2025
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Updates dev branch with latest release (b6314) from ggml-org/llama.cpp