| --- |
| license: apache-2.0 |
| base_model: google/embeddinggemma-2 |
| library_name: mlx |
| pipeline_tag: sentence-similarity |
| tags: |
| - mlx |
| - embeddings |
| - text-embeddings |
| --- |
| |
| # EmbeddingGemma 2, text only, 8-bit MLX |
|
|
| [google/embeddinggemma-2](https://huggingface.co/google/embeddinggemma-2) (revision |
| `914f7f89142e33e77833254d9c9b90c3cef7303b`) with its image and audio encoders removed, for text search on Apple |
| silicon. 320 MB in all, against about 1.27 GB for the 8-bit conversion that keeps |
| the encoders. |
|
|
| - Text tower only (271M of the model's 744M parameters). |
| - Matrices quantized affine, 8 bits, group 64; scales, biases, norms and |
| scalars in bfloat16 (never float16: the model overflows in float16). |
| - 768-dimensional output with Matryoshka prefixes 512, 256 and 128; mean pooling, |
| L2 normalization. Use the source model's prompts, for example |
| `task: search result | query: …` and `title: none | text: …`. |
| - The tokenizer and the sentence-transformers configs are Google's files, byte for |
| byte. |
|
|
| Converted by RuniT-ChatFramework's `Scripts/convert-embeddinggemma2-text.py`. Its |
| vectors match the FP32 reference cosines of Google's checkpoint within 0.002 on |
| multilingual query and document pairs, the same as the 8-bit build with encoders. |
|
|
| License: Apache 2.0, as the source model |
| (https://ai.google.dev/gemma/docs/gemma_4_license). |
|
|
