model-conversion : add support for SentenceTransformers (#16387)

* 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.
This commit is contained in:
Daniel Bevenius
2025-10-09 14:35:22 +02:00
committed by GitHub
parent 2c0d875ae6
commit 56b4795842
9 changed files with 297 additions and 140 deletions

View File

@@ -189,6 +189,23 @@ This command will save two files to the `data` directory, one is a binary
file containing logits which will be used for comparison with the converted
model, and the other is a text file which allows for manual visual inspection.
#### Using SentenceTransformer with numbered layers
For models that have numbered SentenceTransformer layers (01_Pooling, 02_Dense,
03_Dense, 04_Normalize), use the `-st` targets to apply all these layers:
```console
# Run original model with SentenceTransformer (applies all numbered layers)
(venv) $ make embedding-run-original-model-st
# Run converted model with pooling enabled
(venv) $ make embedding-run-converted-model-st
```
This will use the SentenceTransformer library to load and run the model, which
automatically applies all the numbered layers in the correct order. This is
particularly useful when comparing with models that should include these
additional transformation layers beyond just the base model output.
### Model conversion
After updates have been made to [gguf-py](../../gguf-py) to add support for the
new model the model can be converted to GGUF format using the following command:
@@ -208,6 +225,13 @@ was done manually in the previous steps) and compare the logits:
(venv) $ make embedding-verify-logits
```
For models with SentenceTransformer layers, use the `-st` verification target:
```console
(venv) $ make embedding-verify-logits-st
```
This convenience target automatically runs both the original model with SentenceTransformer
and the converted model with pooling enabled, then compares the results.
### llama-server verification
To verify that the converted model works with llama-server, the following
command can be used: