GLM-5.2 ships the DSA "lightning indexer" on only a subset of layers (the
"full" layers; others omit it), but the GLM_DSA loader created the five
indexer tensors on every layer as required, so loading any GLM-5.2 GGUF
failed with e.g. `missing tensor 'blk.3.indexer.k_norm.weight'`.
GLM_DSA's graph is llama_model_deepseek2::graph (plain MLA) and does not use
the indexer tensors (indexer runtime not yet implemented), so they are
loaded-but-unused. Marking them TENSOR_NOT_REQUIRED lets layers without an
indexer load as nullptr and the model runs as full MLA attention.
DeepSeek-V3.2 (uniform indexer on all layers) is unaffected.
* Make ggml_gated_delta_net take only the initial recurrent state (D, 1, n_seqs) and passes the snapshot count K as an op parameter instead of inferring it from state->ne[1].
Remove the padding hack and copy all emitted snapshots into the recurrent cache with a single strided ggml_cpy
* Make GDN changes in all backends. Address review comments.
* Fix CI build errors
* llama-graph : apply embedding scale when deepstack is not used
* nits: remove non-existant hunyuan-vl from the tests
* apply suggestion from @gabe-l-hart
---------
Co-authored-by: Xuan Son Nguyen <[email protected]>
A SWA-only draft head (e.g. StepFun MTP) leaves the base sub-cache
empty, so its kq_mask buffer stays null and asserts at load. Guard
each mask on its own buffer in set_input and can_reuse, base and swa.
Co-authored-by: Georgi Gerganov <[email protected]>
A fitted target context can end up smaller than the draft default, the
oversized assistant views then overflow the shared K/V tensors and trip
the ggml_view_4d size assert during graph reserve.
* feat(convert): Get language model conversion working for 4.1 vision
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat(convert): Skip multimodal tensors for GraniteMoeHybrid (vision 4.0)
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Disable vocab padding for non-hybrid models that use GraniteMoeHybrid
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Plumb python-side vision projector names and mappings
There are several awkward things here:
1. Most of these are essentially identical to the audio qformer tensors. On
the c++ side, that's mapped using the prefix, so the rest of the GGUF
name needs to align, but on the python side there's no prefix notion, so
they all get duplicated.
2. There are a couple of net-new tensors for vision, in particular
PROJ_NORM. In both speech and vision, the QF_PROJ_NORM is qualified as
belonging to the qformer portion, but the GGUF name is simply proj_norm
which conflicts with the ideal name for this new PROJ_NORM that is not
qualified as part of the qformer. To get around this, I used
"proj_layernorm" as the GGUF name.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add python side architecture name
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add python-side plumbing for setting FEATURE_LAYERS hparam
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add c++ side tensor naming defines
NOTE: Usage of these hasn't been updated to include prefix yet
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat(mtmd): Convert vision_feature_layer to an ordered vector
We need to preserve the ordering of these feature index values so that they
can be mapped to the sub-tensors within the stacked projectors.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat(mtmd): Add architecture label plumbing
Branch: Granite4Vision
AI-usage: full (OpenCode + qwen3.5:122b)
Signed-off-by: Gabe Goodhart <[email protected]>
* feat(wip): Add partial conversion for mmproj
This handles stacking the projector tensors and setting the new harams
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add gguf_writer and constant support for new hparams and deepstack layer arr
Branch: Granite4Vision
AI-usage: draft (OpenCode + qwen3.5:122b)
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Full conversion for mmproj w/ tensor mappings
Branch: Granite4Vision
AI-usage: full (OpenCode + qwen3.5:122b)
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Add lm_head skip for mmproj for 4.0
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: De-alias text_config architecture in convert_lora_to_gguf.py
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add --trust-remote-code arg to convert_lora_to_gguf.py
This defaults to False, but allows a user to enable it programmaticly
instead of using the interactive prompt.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: De-alias model.language_model. -> model. for lora adapters
Branch: Granite4Vision
AI-usage: full (OpenCode + qwen3.5:122b)
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Extend language model tensor dealiasing in adapters
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove unnecessary registration for GraniteSpeech in language model
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Plumb through mm prefix formatting for qformer tensors
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Refactor vision projector tensors to use predictor ID as the block
This is cleaner than stacking them. The modeling file hard-codes
single-layer qformers, so we can punt on the multiipule multi-layer
projectors problem.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add spatial offests array hparam conversion
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add stub plumbing for granite vision in mtmd
Branch: Granite4Vision
AI-usage: draft (OpenCode + qwen3.5:122b)
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add new hparam and tensor naming in clip-impl.h
New hparams:
- KEY_PROJ_SAMPLE_QUERY_SIDE
- KEY_PROJ_SAMPLE_WINDOW_SIDE
- KEY_PROJ_SPATIAL_OFFSETS
New tensors:
- TN_MULTI_PROJ_IMG_POS
- TN_MULTI_PROJ_QUERY
- TN_MULTI_PROJ_LAYERNORM
- TN_MULTI_PROJ_LINEAR
- TN_MULTI_PROJ_NORM
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Move deepstack_layer_arr to llm hparam instead of mmproj
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove IS_DEEPSTACK_LAYERS
This appears to have been added during Qwen3 VL
(https://github.com/ggml-org/llama.cpp/pull/16780), but it was never
actually used.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: n_deepstack_layers -> deepstack_layer_arr
The old logic hard coded a correspondence between the first N layers of the
LLM and the 1->N entries in the input embeddings. Now, that relationship is
maintained at loading time if the GGUF value is single-valued. If it is
multi-valued, it loads directly allowing for deepstack layers to be spaced
out throughout the model.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Use try/catch for single/multi valued deepstack info
The alternative would be to use get_key_or_arr, but then the single value
would be populated through the entire array and we'd need to detect that
and update it with the right correspondence.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add deepstack injection point for granite LLM
The use of ggml_add here assumes that the elements of inp_embd will be pre-
arranged to be the full embedding length with only the vision-mask'ed
portions non-zero from the projector. This matches how Qwen3VL does it.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: add missing vision attn layernorm eps
Branch: Granite4Vision
AI-usage: full (OpenCode + Qwen 3.6-35B)
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Hoist qformer tensors into qf_block and hold a vector for multi-proj
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Fix missing prefix template for TN_QF_PROJ_LINEAR
It's not strictly necessary since vision uses the blockwise version, but it
makes the loading consistent.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Add embedding scale and image grid pinpoints hparams in conversion
Also remove dead parsing for self._deepstack_layer_arr
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add mtmd KEY_ section for hparams shared with the LLM
In this case, we need the EMBEDDING_SCALE so we can unscale the image
embeddings to compensate for applying embedding scale to the input
embeddings
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Implement c++ hparam parsing
Branch: Granite4Vision
AI-usage: draft (Claude Code)
Co-authored-by: Eli Schwartz <[email protected]>
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Flatten pinpoints in conversion
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Add missing break
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: No reason to have modality prefix for img_pos
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add tensor loading
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix(convert): Fix confusion between proj.norm and proj.qformer.layernorm
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Use the right portion of speech for tensor loading!
Also plumb through the layernorm -> post_norm naming change
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add logging of deepstack_layers_arr if set
I also changed the print_f output type to int32_t to avoid printing
overflow values for -1. This could cause overflows on the other side, but
I can't imagine a value for any of the current array hparams that would
trigger that.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Make sure input embeddings are cont before f_embedding_scale
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add init and mmproj_embd cases for g4v
The n_mmproj_embd is 1+ to make space for the text embedding and all 8
projectors
Branch: Granite4Vision
AI-usage: draft (Bob)
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Invert (h, w) -> (w, h) pinpoints
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Reorder projectors based on llm index and skip the first injection
The multi-projector stack has a strange asymmetry based on how it's
currently implemented for qwen3vl: on the mmproj side, it's all N
projectors, but the output of the "first" (by inp_embd index) projector is
automatically consumed as if it were a standard single-projector mmproj,
so the deepstack portion needs to only contain the 1-N entries.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
Co-authored-by: Eli Schwartz <[email protected]>
* fix: Fix mmproj hparams in conversion
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
Co-authored-by: Eli Schwartz <[email protected]>
* fix: Fix ordering/logic for deepstack injection in granite
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
Co-authored-by: Eli Schwartz <[email protected]>
* fix: Fix preprocessing config to match what the model needs
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
Co-authored-by: Eli Schwartz <[email protected]>
* wip: Partial port of Eli's implementation
This is still pretty broken, but it's getting closer. It now happily
generates tokens, but the values are quite incorrect still. I suspect it's
caused by the mapping of projectors from safetensors to their respective
orders here.
Also, this implementation breaks encapsulation pretty badly in mtmd_encode.
This will need a big refactor to put the G4V-specific encoding logic
somewhere more appropriate.
Branch: Granite4Vision
AI-usage: draft (Claude Code, Bob)
Signed-off-by: Gabe Goodhart <[email protected]>
Co-authored-by: Eli Schwartz <[email protected]>
* fix: Fix the pre-scaling on the input embeddings to correctly invert the scale
We've got tokens! They still don't line up quite right, so something's a
little off, but we're getting much closer now.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: invert embedding multiplier -> base_scale at load
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Fix setting image_resize_pad after new enum introduced
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Add G4V to mmproj mapping in conversion
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Re-add padding disable for non-hybrid hybrid models
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Simplify G4V n_tokens computation
This is slightly more efficient and flexible for when we implement the
unpad cropping. IMO, it's also clearer that it is adding the number of
image_newline tokens (embeddings) to the grid, rather than recomputing the
entire count.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add new clip APIs for post-tile-encoding assembly
Granite 4 Vision uses llava-next style pack-and-unpad which requires
injecting the learned newline after each row of the tile grid. A row here
is a single row of the grid which is composed of (grid_x * cols_per_tile) *
(grid_y * rows_per_tile), so the result is newlines injected in between
individual tile rows, thus not something that can be handled with the
standard llava-uhd block-wise endcoding.
Branch: Granite4Vision
AI-usage: draft (Claude Code + Opus 4.7)
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Add model interfaces for granite 4 vision assembler
I'm on the fence about the best organization of this. These free functions
allow the per-architecture logic in clip.cpp to access the model-specific
graph building, but they still require a fair bit of model-specific logic
in clip.cpp which is not ideal.
I think a better approach may be to replicate what is done with the
graph builders themselves (and possibly even make the assembler part of the
model's existing graph builder).
Branch: Granite4Vision
AI-usage: full (Claude Code + Opus 4.7)
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Remove all g4v-specific branching from mtmd.cpp in favor of clip assembler
Branch: Granite4Vision
AI-usage: full (Claude Code + Opus 4.7)
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor(mtmd): Consolidate assembler logic into clip_assembler class family
Just like `clip_graph` is the base class for building the model-specific
encoder graphs, `clip_assembler` will be the base class for building the
model-specific assembler graphs. This allows the assembly pattern to follow
how the encoder pattern is implemented where the model-specific logic lives
in a subclass co-located with the encoder graph builder that gets
constructed by a simple factory method.
Branch: Granite4Vision
AI-usage: full (Claude Code + Opus 4.7)
Signed-off-by: Gabe Goodhart <[email protected]>
* style: Comment improvement
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: granite_vision -> granite4_vision
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove dead codepath for Qwen3VL add_vision_is_deepstack
These pieces were never used on the c++ side (removed there in an earlier
commit), so this is just cleanup that I missed before.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Oops! I did not mean to commit one of my prompt files
But now it's too far back in history to effectively rebase out, even with
interactive and --rebase-merges :(
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Add missing <algorithm> include for std::find
It seems that this was already pulled in on some platforms, but not on
others
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Fix Flake8 warnings in granite conversion module
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Remove clip_assembler in favor of clip_image_f32.append_token
Per conversation in the PR, the clip_assembler pattern was too invasive.
This is a compromise that limits model-specific blocks to add_media where
each preprocessed tile is annotated with an injection type, after which all
the token counting logic is generic and the newline injection itself is
handled in the graph based on the value for the given tile image.
Branch: Granite4Vision
AI-usage: draft (Bob, OpenCode + Qwen 3.6 35b)
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor(convert): Split n_deepstack_layers and deepstack_layers (array)
Branch: Granite4Vision
AI-usage: full (Bob, OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor(src): Handle n_deepstack_layers and deepstack_layers GGUF keys
Branch: Granite4Vision
AI-usage: draft (Bob, OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Fix GGUF key for deepstack_layers_arr
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Remove pre-scaling embeddings and skip scaling for raw embd inputs
This follows how gemma3 and gemma4 handle embedding scaling by skipping the
multiplier for raw input embeddings.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: deepstack_layers(_arr) -> deepstack_mapping(_arr)
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Fully revert changes to n_deepstack_layers and qwen3vl*
Since we're going to keep the GGUF KVs separate, it makes sense to just
keep the hparams separate too to limit the scope of this branch. The down
side is that n_deepstack_layers and deepstack_mapping_arr are potentially
conflicting.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Revert removal of "is_deepstack_layers" GGUF KV
This KV is not used at all on the c++ side, so it's fully dead, but there's
also no need to conflate this cleanup with the addition of G4V.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove unnecessary ggml_cont and build_forward_expand in cbx
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* style: Clean up comments
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Tighter and more flexible code for g4v_build_block
This could be refactored to look a lot more like granite-speech, but the
overall block constructs before/after the qformer are pretty different, so
for now I'm going to leave it as is and just tighten a bit.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove unnecessary `unordered_set` include
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Add architecture guard on deepstack_mapping_arr printout
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove unnecessary AI-gen comment
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Always initialize deepstack_mapping_arr with -1 values
This was causing `test-llama-archs` to fail, likely due to trying to save
the uninitialized values, then re-loading them. It's safer to always
initialize so that other models don't forget and end up with undefined
behavior.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* style: Remove TODO about block/vs non-block tensor mapping
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Move is_vision_feature_layer logic into clip_hparams
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Use a bool for append_token
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* style: Remove unnecessary comment
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Remove unused get_model api
yikes!
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: Rearrange helpers for g4v to be private members and use build_attn
Branch: Granite4Vision
AI-usage: full (Bob, OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Fix off-by-one in vision layer index
This was inherited from the Claude Code implementation that pushed the
negative index inversion down into the model file.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Fix norm/post_norm mixup in conversion
face. palm. :(
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* style: More descriptive tensor names
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* fix: Apply PR cleanup for new conversion changes
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
Co-authored-by: Sigbjørn Skjæret <[email protected]>
* fix(convert): Remove duplicate V_ENC_EMBD_IMGNL
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* refactor: append_token -> add_newline
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* style: Comment cleanup
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
* feat: Cleaner error handling/checking
NOTE: format_string is not available in granite.cpp (and including
clip-impl.h to get it doesn't compile, so I think it violates the intended
encapsulation), so std::stringstream is the simplest answer.
Branch: Granite4Vision
AI-usage: none
Signed-off-by: Gabe Goodhart <[email protected]>
---------
Signed-off-by: Gabe Goodhart <[email protected]>
* 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)
* speculative : add common_speculative_n_max helper function
Extract the speculative max-draft-size logic from server_n_outputs_max
into a reusable common_speculative_n_max() function in common/speculative.
Assisted-by: llama.cpp:local pi
* cont : draft context always has n_parallel outputs
* llama : log n_outputs_max
* speculative : remove draft-simple auto-enable
* ci : enable server tests on PRs
* llama: save more VRAM by reserving n_outputs == n_seqs when possible
* add n_outputs_per_seq
* move n_outputs_max to server-context
* change ubatch to batch everywhere
Tarek Dakhran
Tim Neumann
YiChen LvandAman Gupta
Adrien Gallouët
davidrhodus
Ruixiang WangandGeorgi Gerganov
Dev-iL
Oliver Simons
Bartowski
Michael WandandSigbjørn Skjæret
o7siandSigbjørn Skjæret
Gaurav Garg
Aarnav PaiandXuan Son Nguyen
Max Krasnyansky
PascalandGeorgi Gerganov
Gabe Goodhart
Johannes Gäßler
Mikhail PodvitskiiandSigbjørn Skjæret
Hans Florian
Piotr Wilkin (ilintar)andSigbjørn Skjæret
Junwon HwangandLG-AI-EXAONE
Ruben Ortlam