vrr/koboldcpp
2
0
Fork 0
mirror of https://github.com/LostRuins/koboldcpp.git synced 2026-05-09 19:46:11 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

model : Qwen3 Next (#16095)

Browse source 
* Qwen3 Next - cleaned up version

* Whitespaces and stuff

* Correct minor errors

* Update src/llama-model.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Misc. fixes.

* Clean up code, add missing hybrid qualifier

* Did someone transpose the SOLVE_TRI result matrix? Perhaps...

* Whitespace

* Proper tensors for cb calls

* Use llama-graph.h vertical alignment

* BROKEN: chunking

* Set new tensors as inputs.

* Proper chunk logic

* It's the circle of life...

* More shenanigans for n_seq > 1

* Nail in the coffin?

* Fix Windows build

* Eh, one fails on Windows, the other fails on Mac... just use general capture.

* quant : cleanup

* model : cleanup

* qwen3 : cleanup

* cont : cleanup

* cont : cleanup

* ggml : revert change

* qwen3 : cleanup

* cont : cleanup

* Readd cmath

* qwen3 : fix typo

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Usual suspects

* fix my bad suggestion

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Piotr Wilkin (ilintar) 2025-11-28 12:02:56 +01:00 • committed by GitHub
parent 73955f7d2a
commit ff55414c42
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
16 changed files with 1345 additions and 19 deletions
Download patch file Download diff file Expand all files Collapse all files

4
src/llama-context.cpp
View file

@ -1,5 +1,6 @@
#include "llama-context.h"
#include "llama-arch.h"
#include "llama-impl.h"
#include "llama-batch.h"
#include "llama-io.h"
@ -1386,6 +1387,9 @@ void llama_context::output_reorder() {
//
uint32_t llama_context::graph_max_nodes() const {
if (model.arch == LLM_ARCH_QWEN3NEXT) {
return std::max<uint32_t>(8192u, 32u*model.n_tensors());
}
return std::max<uint32_t>(1024u, 8u*model.n_tensors());
}