| --- |
| 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. |
|
|
