* llama : add support for NVIDIA Nemotron Nano 3
This commit adds support for the NVIDIA Nemotron Nano 3 model, enabling
the conversion and running of this model.
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* kv-cache : fix state restore with fragmented cache (#17527)
Change find_slot to allow non-contiguous allocation during state restore. Fixes 'failed to find available cells in kv cache' error when restoring state to fragmented cache.
* tests : update logic
* cleanup: tightened state_read_meta sig, added is_contiguous case
* fix: state_read_meta arg reorder loose ends
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama: automatically fit args to free memory
llama-fit-params tool
* fix CI
* hints for bug reports, ensure no reallocation
* fix segfault with Vulkan
* add llama-fit-params to CI
* fix CI
* fix CI
* fix CI
* minor adjustments
* fix assignment of 1 dense layer
* fix logger not being reset on model load failure
* remove --n-gpu-layer hint on model load failure
* fix llama-fit-params verbosity
* fix edge case
* fix typo [no ci]
PR #17091 set the VERSION of various libraries to 0.0.abcd, where abcd
is the LLAMA_BUILD_NUMBER. That build number is too large to fit in the
Mach-O 'current version' field's 'micro' part, which only goes up to
255. This just sets the Mach-O current version to 0 to get it building
properly again.
Fixes#17258.
* Make graph_max_nodes vary by ubatch size for models where chunking might explode the graph
* Update src/llama-context.h
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add missing const
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : remove quantization sanity check
This commit removes the quantization sanity check for attention layers.
The motivation for this is that there are model that are hybrid models
that have recurrent layers, experts layers, and attention layers. For
these models the current check fails as the experts layers are not
taking into account. After consideration, it was decided that this check
is not strictly necessary, and can be removed to allow for more flexible
model architectures.
* llama : remove unused pruned_attention_w and is_clip_model vars
Add nosubs|optimize flags to std::regex constructors to prevent
catastrophic backtracking when processing prompts with repeated
identical characters (e.g., 'A' * 10000).
The nosubs flag disables subgroup capture, significantly reducing
memory usage and backtracking on uniform token sequences
Daniel Bevenius