- Add threading support implementation details
- Document ThreadPoolExecutor usage and thread safety
- Add model parameter implementation details
- Include testing results for both features
- Add ThreadPoolExecutor for parallel request processing controlled by --threads
- Add --model argument to specify model name in request data
- Refactor process() to use thread-safe _process_single_case() method
- Update progress tracking to work with concurrent execution
- Create new simplified evaluation script focused only on AIME
- Implement EvalState and Processor dataclasses for structured state management
- Add real-time feedback showing correct/incorrect status per case
- Abstract grading interface for external grader support
- Use structured JSON output for eval state
- Apply HuggingFace dataset caching to avoid repeated downloads
- Remove Levenshtein matching - eval script only sends requests and validates answers
Extract repeating question string into TEST_QUESTION variable and
create make_request() helper function to reduce code duplication.
Add proper error handling for error responses.
Add a standalone Python script that simulates a llama-server HTTP endpoint
for testing the eval script. The simulator:
- Implements /v1/chat/completions endpoint with OpenAI-compatible format
- Loads AIME dataset from HuggingFace with local caching
- Uses Levenshtein distance for intelligent question matching
- Supports configurable success rate for correct/wrong answer generation
- Provides debug logging for troubleshooting
Also includes test scripts and documentation for testing and understanding
the simulator functionality.
The error:
./examples/sycl/test.sh: line 122: level_zero:${$GGML_SYCL_DEVICE}: bad
substitution
was thrown whenever the user used this command:
./examples/sycl/test.sh -mg 0
Fix is to get rid of a dollar sign.
* port #22358 PR to examples/speculative/speculative.cpp
* use vocab_[tgt,dft] instead of ctx_[tgt,dft] when logging on draft
model / target model vocabulary mismatch
Co-authored-by: Petros Sideris <petros.sideris@nokia.com>
* common: refactor common/debug to move abort_on_nan into base_callback_data
Passing bool abort_on_nan as template parameter for common_debug_cb_eval is unnecessary and creates an issue with LTO.
It should just be a member of the base_callback_data instead.
* cont : cleanup
* common : use pimpl in debug.h to reduce header dependencies
Move common_debug_cb_user_data's data members (std::regex,
std::vector<uint8_t>) into a private impl struct in debug.cpp.
This removes the includes of common.h and <regex> from debug.h,
reducing transitive dependencies for any translation unit that
includes the header.
Assisted-by: llama.cpp:local pi
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* opt arc770 for Q4_0
* add for Q4_0
* update the script
* add help script for windows
* update guide
* fix format issue
* convert from dos to unix for format issue
* fix missed -sm parameter
* model-conversion : fix mmproj output file name [no ci]
This commit updates the convert-model.sh script to properly handle
mmproj output files.
The motivation for this that currently the same name as the original
model is used as the mmproj file, which causes the original model to
be overwritten and no mmproj-<model_name>.gguf to be created.
* model-conversion : use MODEL_NAME [no ci]
* requirements : update transformers to 5.5.0
This commit updates the transformers dependency to version 5.5.0.
The motivation for this is that transformers 5.5.0 includes support for
Gemma4 and is required to be able to convert Gemma4 models. This is also
causing issues for user of gguf-my-repo.
Refs: https://huggingface.co/spaces/ggml-org/gguf-my-repo/discussions/202
* fix huggingface_hub version
* set version of transformers to 5.5.0
* convert : add ty ignore directives to convert_hf_to_gguf.py
This commit adds `ty: ignore` directives to transformers tokenizers
field/methods to avoid type check errors. There might be better ways to
handle this and perhaps this can be done in a follow up commit.
The motivation for this is that it looks like in transformers 5.5.0
AutoTokenizer.from_pretrained can return generic tokenizer types or None
and the type checker now produces an error when the conversion script
accesses field like tokenizer.vocab.
* convert : add ty ignore to suppress type check errors
* convert : remove incorrect type ignores
* convert : fix remaining python checks
I was running a newer version of ty locally but I've switched to
version 0.0.26 which is what CI uses and I was then able to reproduce
the errors. Sorry about the noise.
* update transformers version to 5.5.1
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.
The build info is now only for debug, so we avoid the duplicate
with `--version`.
The UTF-8 setup at the beginning is needed to avoid logging
garbage on Windows.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
