---
license: apache-2.0
base_model:
- google/embeddinggemma-2
base_model_relation: quantized
pipeline_tag: feature-extraction
tags:
- radiance
- embeddings
- multimodal
- sentence-similarity
- bf16
---

# EmbeddingGemma 2 — radiance container (bf16)

[google/embeddinggemma-2](https://huggingface.co/google/embeddinggemma-2) packed, **unchanged in
precision**, into a single `.rad` container for the
[radiance](https://codeberg.org/StillDeadcode/radiance) inference engine. Every weight stays bf16 as
the checkpoint ships it. This is an unofficial conversion; the model is Google DeepMind's, released
under Apache 2.0 (see `LICENSE` and the [original model card](https://huggingface.co/google/embeddinggemma-2)).

| | |
|---|---|
| File | `embeddinggemma2-bf16.rad` — 1,502,429,184 bytes (1.39 GiB of weights, 1257 tensors) |
| SHA-256 | `d46988383e41de05df1ff69f491b1a6351a2ab69d26771943ca150768115bdae` |
| Source | `google/embeddinggemma-2` at revision `914f7f89142e33e77833254d9c9b90c3cef7303b` (`model.safetensors` SHA-256 `197a32965d4b1105faf060417baa899e193fb73cd401f42ec9295234d5553d79`) |
| Output | 768-dimensional pooled vectors (Matryoshka: `dimensions` may truncate) for text, images, video and audio |
| Engine | radiance 1.2.4 or later (embedding support); made and tested with 1.3.0 |

## Serve

The model runs on the CPU (about 0.25–1.5 GiB of RAM) or on one GPU:

```sh
radiance --model embeddinggemma2-bf16.rad --host 0.0.0.0 --port 8000 --api-key "$KEY"
```

```sh
curl -s http://localhost:8000/v1/embeddings -H "Authorization: Bearer $KEY" \
  -H 'Content-Type: application/json' \
  -d '{"input":"free space path loss at 6 GHz","prompt_name":"query","dimensions":256}'
```

## How this file was made

Converted with `rad-convert` from the official radiance image
`docker.io/stilldeadcode/radiance:1.3.0@sha256:641f2d8dc30f26dcd42673916a480bb5d1a71b28de8cd5e7fb77b47f77251b8c`,
with no quantisation recipe, so every weight keeps the checkpoint's encoding:

```sh
rad-convert ./embeddinggemma-2 --tokenizer ./embeddinggemma-2/tokenizer.json \
  -o embeddinggemma2-bf16.rad
```

`./embeddinggemma-2` is the source repository at the revision above. The conversion is
deterministic: running it again produces a byte-identical file with the SHA-256 above.

## License

Apache License 2.0, as the original model. Copyright for the model belongs to Google DeepMind.