* model-conversion : add support for SentenceTransformers
This commit adds support for models that use SentenceTransformer layers.
The motivation for this is that if converted model includes any of the
numbered layers specified in the original models repository then these
changes enable these models to be used and verified. Currently the
model-conversion only support the base model output without any of
the additional transformation layers.
Usage:
Convert the model that also includes the SentenceTransformer layers:
```console
(venv) $ export EMBEDDING_MODEL_PATH="~/google/embeddinggemma-300M"
(venv) make embedding-convert-model
```
Verify the produced embeddings from the converted model against the
original model embeddings:
```console
(venv) make embedding-verify-logits-st
```
The original model can be run using SentenceTransformer:
```console
(venv) make embedding-run-original-model-st
```
Run the converted model using "SentenceTransformer" layers whic
enables pooling and normalization:
```console
(venv) make embedding-run-converted-model-st
```
* add model-conversion example requirements
* add support for -st flag in embedding model conversion
This commit add support for the -st flag in the embedding model
conversion script. This will enable models to be converted using
sentence transformers dense layers.
* sampler: turn lazy grammar trigger words to regexes
* add scripts/tool_bench.sh & .py
* constrain llama json output regardless of function name if matches at beginning
* update relaxed newline space rule in grammar tests
* support add_generation_prompt query parameter (useful for /apply_template)
* Update src/llama-grammar.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* py : type-check all Python scripts with Pyright
* server-tests : use trailing slash in openai base_url
* server-tests : add more type annotations
* server-tests : strip "chat" from base_url in oai_chat_completions
* server-tests : model metadata is a dict
* ci : disable pip cache in type-check workflow
The cache is not shared between branches, and it's 250MB in size,
so it would become quite a big part of the 10GB cache limit of the repo.
* py : fix new type errors from master branch
* tests : fix test-tokenizer-random.py
Apparently, gcc applies optimisations even when pre-processing,
which confuses pycparser.
* ci : only show warnings and errors in python type-check
The "information" level otherwise has entries
from 'examples/pydantic_models_to_grammar.py',
which could be confusing for someone trying to figure out what failed,
considering that these messages can safely be ignored
even though they look like errors.
