llama.cpp

bfb4308b - model : support granite multilingual embeddings R2 (ibm-granite/granite-embedding-{97,311}m-multilingual-r2) (#22716)

model : support granite multilingual embeddings R2 (ibm-granite/granite-embedding-{97,311}m-multilingual-r2) (#22716) * Add support for the ibm-granite/granite-embedding-{97m,311m}-multilingual-r2 embedding models: * Added a version of the gpt4o tokenizer that has a fixed regex (better handling of marks), and different token merging setting for the 97m model * Reused gemma4 tokenizer for the 311m model * granite-embedding-*-multilingual-r2 : add support SwiGLU FFN for Granite Embedding Multilingual R2 * added new GGUF key <arch>.hidden_activation (LLM_KV_HIDDEN_ACT) + writer * added a forward declaration of llm_ffn_op_type to llama-hparams.h * added llm_ffn_op in hparams * added LLM_FFN_NONE = 0 sentinel to llm_ffn_op_type (value-initialization), modern-bert: explicitly assigns LLM_FFN_GEGLU before reading GGUF (unchanged). * centralized hidden_act mapping in llama-model.cpp, added llm_ffn_op_type_from_string() helper, mirroring rope_scaling_type/llama_rope_scaling_type_from_string() * modern-bert reads the GGUF key (when present) and uses the resulting op in its FFN graph * Added granite-embedding-{97m,311m}-multilingual-r2 to the converter code * Added the hashes for the granite embedding multilingual R2 models * Set the hidden_activation in the GGUF if the field is present in config.json (such as for the granite embedding models)