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change to a flatter directory structure and group the options with the
function

update models to call rope in one place

This change:

* fixes rope scaling in the mistral converter
* updates ministral to include llama4 scaling
* includes a new ministral parser for parsing reasoning and tool calling

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Co-authored-by: jmorganca <jmorganca@gmail.com>

the check for mla omits v3 and r1 which should not return unsupported.
instead check the tokenizer for compatibility

* Add mla for flash attention
* Revert to using chunks

* use slice/chunks

* bert

* llama4

* gemma3n

* gptoss

* mistral3

* qwen3vl

* qwen25vl

* deepseek2

* remove unused ops

* ml(ggml): mrope
* interleave mrope

this change fixes images with an alpha channel by overlaying the image
onto a white background

Co-authored-by: Michael Yang <git@mxy.ng>

deepseek's qwen3 distill uses a different rope scheme so support both

* init deepseek model file

* temp removal of flash attention implementation

* shapes and proper, can make a pass

* query, key, value have good cosine similarity, but the max diff is a bit high

* Attention block is working! ** with eager for now, have not added the mask line

* Attention block is working! ** with eager for now, have not added the mask line

* working MoE at around 0.95 cosine sim

* added cosine similarity function

* Starting end to end structure

* Trying (and failing) to get rope to work, going to test full thing on tater

* running on tater36... just not the right outputs

* we have the right values for rope... but its still not working?

* chnage Extrapolation Factor to 1

* removed adding residuals twice, removed normalization from shared expert, refactored Norms (Attention, MLP) to be outside the (Attention, MLP) blocks and in the Transformer block instead, add cache setLayer

* Temporary modelfiles for cpu

* change kpass intermediate step to kv, two layer outputs [0,1] look fine

* this calls for 16 chicken nuggets

* whoops

* cleaning up code

* delete stuff we dont need

* getting rid of debug statements for llama cpp

* working with long contexts

* fix long context view error

* reverting some changes I made for files that are not apart of pr

* Added proper tokenizer for deeepseek3

* clean up model and go test

* remove Modelfile

* not passing the tests

* whoops

* how to pass the ci tests

* resolving some of the comments

* rename

* linted and renamed deepseek3 -> deepseek2

* remove name go

* addressed changes - main change was adopting qwen3 naming scheme

* I cannot with linters

* clean up logs

* clean up logs

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Co-authored-by: Grace Guo <graceguo@Graces-MBP.localdomain>
Co-authored-by: Grace Guo <graceguo@Graces-MacBook-Pro.local>
Co-authored-by: graceguo <graceguo@tater36.localdomain>

* gemma: fix rope scaling for qat models

* gofumpt yourself

* cleanup

* use pooling.TypeNone

* pooling test

* qwen3 embed

* fix(llama): rope scale

* spm llama

* skip moe models

* cleanup

* use ggml_*_split activations when possible

* forward qkv

* cleanup

* use pooling.TypeNone

* pooling test

* 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

* ollama: add embeddings

* perf: build graph for next batch in parallel to keep GPU busy

This refactors the main run loop of the ollama runner to perform the main GPU
intensive tasks (Compute+Floats) in a go routine so we can prepare the next
batch in parallel to reduce the amount of time the GPU stalls waiting for the
next batch of work.

* tests: tune integration tests for ollama engine

This tunes the integration tests to focus more on models supported
by the new engine.