This commit updates the debug example to not create the
base_callback_data.
The motivation for this is when using `--save-logits`, which is used by
examples/model-conversion scripts, we often don't care about the tensor
outputs and they just add noise to the output. This changes is quiet by
default we can always remove --save-logits to get the tensor outputs
when debugging.
* feat: support step3-vl-10b
* use fused QKV && mapping tensor in tensor_mapping.py
* guard hardcoded params and drop crop metadata
* get understand_projector_stride from global config
* img_u8_resize_bilinear_to_f32 move in step3vl class
* Apply suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* fix the \r\n mess
* add width and heads to MmprojModel.set_gguf_parameters
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Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* webui: fix syntax highlighting lost for non-common languages after streaming
rehype-highlight uses lowlight internally, which only bundles 37 "common"
languages. The streaming code path uses highlight.js directly (192 languages),
so languages like Haskell highlight correctly while streaming but lose all
color once the code block closes. Pass the full lowlight language set to
rehype-highlight so both paths support the same languages.
* webui: rebuild static files after rebase
* ds_read_b128 for q4_0 and q4_1 mmq kernels
Current for loop generates ds_read_b32 instructions with hip compiler, the new solution generates ds_read_b128 instructions for the same operation, saving some LDS bandwidth. Tested on MI50 and RX6800XT, its faster on both.
* Vectorized lds load update: used ggml_cuda_get_max_cpy_bytes and ggml_cuda_memcpy_1 functions for generic implementation
* Explicit for loop in mmq, renamed vec into tmp
* Fixed max_cpy usage in the loading loop
* Fixed typo in q4_1 kernel
* Update ggml/src/ggml-cuda/mmq.cuh
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/mmq.cuh
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/mmq.cuh
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Renoved trailing white line 500
* Update mmq.cuh removed other whitelines
* Remove trailing whitespaces
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Co-authored-by: iacopPBK <iacopPBK@users.noreply.github.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: iacopPBK <iacop@deneb.com>
This commit adds a missing comma in the vision encoder attention qkv
block.
The motivation for this change is that without the comma there will be
a string concatenation of the Kimi-K2.5 and the Nemotron Nano v2 VL
tensor mappings which will be broken.
* Work towards removing bitcast
* Move rest of existing types over
* Add timeout back to wait and remove synchronous set_tensor/memset_tensor
* move to unpackf16 for wider compatibility
* cleanup
* Remove deadlock condition in free_bufs
* Start work on removing parameter buffer pools
* Simplify and optimize further
* simplify profile futures
* Fix stride
* Try using a single command buffer per batch
* formatting
* Add parameters for different browsers in-flight submissions
* Update handling of batch size too
* Throttle ios as much as possible
* Increase timeout for llvm-pipe testing
* unicode : add custom Qwen2 regex handler to fix segfault on long input
std::regex uses recursive backtracking internally, which causes a stack
overflow (segfault) when tokenizing long sequences of repeated characters
(e.g. 43K 'A's). The Qwen2 tokenizer regex differs from Llama3 only in
the digit pattern (\p{N} vs \p{N}{1,3}), so it was falling through to
the std::regex fallback path instead of using a custom handler.
Add unicode_regex_split_custom_qwen2() following the established pattern
used by gpt2, llama3, kimi_k2, and afmoe custom handlers.
Closes: https://github.com/ggml-org/llama.cpp/issues/21113
* cont : remove TODO comment
* cont : update comment to reflect original regex
* use the correct regex in the comment this time... [no ci]
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Co-authored-by: Aldehir Rojas <hello@alde.dev>
Add dequantize4() implementations for Q4_1, Q5_0, Q5_1, and IQ4_NL
in the flash attention base shader. Register them in the shader
generator, pipeline creation, and enable in the scalar/coopmat1 FA
support check.
* Fix Arabic RTL text rendering in web UI
- Add dir='auto' attributes to markdown containers and blocks
- Implement post-processing to add dir='auto' to all text elements
- Replace directional CSS properties with logical properties for proper RTL list alignment
- Ensure bidirectional text support for mixed Arabic/English content
* Clean up commented duplicate function
Remove the commented-out duplicate transformMdastNode function
that was left over from refactoring.
* Fix Arabic RTL text rendering in web UI
- Add dir='auto' attributes to markdown containers and blocks
- Implement post-processing to add dir='auto' to all text elements
- Replace directional CSS properties with logical properties for proper RTL list alignment
- Minor code formatting improvements
This ensures bidirectional text support for mixed Arabic/English content in the llama.cpp web UI.
* Implement rehype plugin for comprehensive RTL text support
- Add rehypeRtlSupport plugin that applies dir='auto' to all elements with children
- Replace DOMParser-based approach with efficient HAST tree processing
- Remove hardcoded element lists for better maintainability
- Ensure proper bidirectional text rendering for mixed RTL/LTR content
* Fix RTL text rendering with rehype plugin and cleanup
* fix: prettier formatting
Extend the existing reorder optimization to Q8_0. The reorder
separates scale factors from weight data for coalesced memory
access -- was implemented for Q4_0/Q4_K/Q6_K but Q8_0 was missing.
On Arc Pro B70 (Xe2), Q8_0 tg goes from 4.88 to 15.24 t/s (3.1x)
on Qwen3.5-27B. BW utilization: 21% -> 66%.
The key fix beyond the kernels: Q8_0 was missing from the type
check in ggml_backend_sycl_buffer_init_tensor() that allocates
the extra struct carrying the reorder flag -- so the optimization
was silently skipped.
AI (Claude) was used to assist with root cause investigation and
writing the kernel code. All code was human-reviewed and tested
on real hardware.
Fixes: #21517
* Write an optimized flash_attn_stream_k_fixup kernel
Write a specialized and more optimized kernel for cases where nblocks_stream_k is multiple of ntiles_dst.
Make nblocks_stream_k to multiple of ntiles_dst if nblocks_stream_k > 2 * ntiles_dst
* Use the new kernel only for nblocks_stream_k_raw > 4 * ntiles_dst to make sure we have enough concurrency on GPUs
* Address review comments
* Address review comments
* Revert variable names to original
Check the return value of sink.write() in the chunked content provider
and return false when the write fails, matching cpp-httplib's own
streaming contract. This prevents logging chunks as sent when the sink
rejected them and properly aborts the stream on connection failure.
This PR changes the logging that occurs at startup of llama-server.
Currently, it is redundant (including CPU information twice) and it is
missing the build + commit info.
