* feat: add Dockerfiles for each platform that user ./server instead of ./main
* feat: update .github/workflows/docker.yml to build server-first docker containers
* doc: add information about running the server with Docker to README.md
* doc: add information about running with docker to the server README
* doc: update n-gpu-layers to show correct GPU usage
* fix(doc): update container tag from `server` to `server-cuda` for README example on running server container with CUDA
* Support for Yi-VL, templating fix for mobileVLM
* ws
* Update examples/llava/clip.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update llava-cli.cpp
* Update clip.cpp
bugfix for new conversions
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
updated the n_task calculation to use max number of
threads possible. This has improved the prompt eval
performance by around 5% for DOT kernels and by
around 10% for MMLA kernels on AWS Graviton3.
* server: add llama_server_queue struct
* server: add llama_server_response_event
* server: add comments
* server: move all mutexes away from server.cpp
* server: correct multitask response
* server: only add back deferred tasks when one slot is available
* server: fix a race condition cause by "request_completion"
* scripts : add lib.sh and lib_test.sh
* scripts : stub out new ci-run.sh script
* scripts : switch to PascalCase for functions
This looks a little odd at first, but I find it very useful as a
convention to know if a command is part of our code vs a builtin.
* scripts : add some fancy conversion from snake_case to PascalCase
* Add venv to ci/run.sh
* Revert scripts work
* scripts : add wrapper script for local use of ci/run.sh
* Simplify .gitignore for tests, clang-tidy fixes
* Label all ctest tests
* ci : ctest uses -L main
* Attempt at writing ctest_with_model
* Update test-model-load-cancel
* ci : add ctest_with_model for debug and release
ggml-ci
* Fix gg_get_model function
ggml-ci
* got stuck on CMake
* Add get_model.cpp to tests/CMakeLists.txt
ggml-ci
* Fix README.md output for ctest_with_model
ggml-ci
* workflows : use `-L main` for all ctest
ggml-ci
* Fixes
* GG_RUN_CTEST_MODELFILE => LLAMACPP_TESTMODELFILE
* Always show warning rather than failing if model file variable is not
set
* scripts : update usage text for ci-run.sh
* implemented dynamic temperature sampling from koboldcpp
* removed trailing whitespace
* removed unused temp parameter in llama_sample_entropy
* exposed exponent_val in dynamic temp sampler
* added debug check for printf statements
* use nullptr in llama_sample_softmax call during llama_sample_entropy
this avoids counting the time taken stats twice
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* return earlier if there is only 1 candiate (i.e. max_entropy == 0)
* reformat 't' case in llama_sample_queue
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* check for one or zero candidates case in llama_sample_entropy
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
this fixes the error I encountered when trying to run the convert.py
script in a venv:
```
$ nix develop
[...]$ source .venv/bin/activate
(.venv)
[...]$ pip3 install -r requirements.txt
<... clipped ...>
[...]$ python3 ./convert.py
Traceback (most recent call last):
File "/home/mhueschen/projects-reference/llama.cpp/./convert.py", line 40, in <module>
from sentencepiece import SentencePieceProcessor
File "/home/mhueschen/projects-reference/llama.cpp/.venv/lib/python3.11/site-packages/sentencepiece/__init__.py", line 13, in <module>
from . import _sentencepiece
ImportError: libstdc++.so.6: cannot open shared object file: No such file or directory
```
however, I am not sure this is the cleanest way to address this linker
issue...
* kl-divergence: be able to save all logits to a file
* Add ability to compute KL-divergence
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* make GGML_TASK_INIT phase can be run in multithread
* multithreaded dequantize in mul_mat when using blas library
* minor fixes
* update outdated comment
* fix coding style
* simplify code
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* MobileVLM native implementation
* delete depthwise_conv_2d and permute_cpy relative code, replace the two by the existed functions, and opt ldp definition, support LLAMA_PERF option for CMake
* move android script to example/llava directory
* Fix the editor config checks
---------
Co-authored-by: Chenxiaotao03 <chenxiaotao03@meituan.com>
* llama : support StableLM 2 1.6B
* convert : fix Qwen's set_vocab wrongly naming all special tokens [PAD{id}]
* convert : refactor Qwen's set_vocab to use it for StableLM 2 too
* nix : add tiktoken to llama-python-extra
* convert : use presence of tokenizer.json to determine StableLM tokenizer loader
It's a less arbitrary heuristic than the vocab size.
This commit adds `--sample-start` and `--include-sample-start` to the
output from the main function in finetune.cpp.
The motivation for this is that even though these are set explicitly by
the user via the command line, if one forgets to set them then it is
useful to have their values printed out. Otherwise it is possible to go
through the whole training process before realizing that the values are
not what one expected.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Add Q3_K_XS - intermediate size between Q2_K and Q3_K_S
* Q3_K_XS: quanize first 1/8 of ffn_down layers with Q4_K
Together with an importance matrix, this brings perplexity
for LLaMA-v2-70B below the perplexity of the former Q2_K
with a 800 MB smaller quantized model size.
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
