GitLab

* use ggml_*_split activations when possible

* forward qkv

* fix truncate

* s/SentencePieceModel/SentencePiece/

* bert

* wordpiece

* refactor pooling

* more tokenizers

* normalize embeddings

this cleans up the model interface slightly without too much impact in
other areas

* Enable CUDA Graphs for gemma3n.

Similar to
https://github.com/ggml-org/llama.cpp/pull/14741,
though ollama has a slightly different model graph
than llama.cpp which requires different workaround
checks.

* Remove residual check by reshaping differently in gemma3n model

This should make the heuristics more robust

* update patches

* cherry pick metal mean kernel

* cherry pick cuda mean kernel

* gemma3n