Bitfarmy/trama-embeddinggemma

EmbeddingGemma 300M for LiteRT (copy used by the Trama browser)

This repository hosts an unmodified copy of two files published by Google in litert-community/embeddinggemma-300m, so that the Trama Android browser can download them, only when the user explicitly enables on-device semantic search. Everything then runs on the phone; no text ever leaves it.

File	Size (bytes)	SHA-256
embeddinggemma-300M_seq256_mixed-precision.tflite	179131736	37115ef7bff76cd37dd86abe503ff511b1032bf85fc624a85c49c84899e92bc5
sentencepiece.model	4683319	d6daa52d93d7aad10e8388bd526c4e501d914b47177398d1d9621f1fe48438c7

The files have not been modified in any way: same bytes as the originals.

License and use restrictions

Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms.

• A full copy of the terms is included in this repository: GEMMA_TERMS_OF_USE.md.
• The use restrictions of section 3.2 and the Gemma Prohibited Use Policy apply to anyone who downloads or uses these files. A copy of the policy is included: GEMMA_PROHIBITED_USE_POLICY.md.
• By downloading or using these files you agree to the Gemma Terms of Use and to the Gemma Prohibited Use Policy, which are binding on you.
• See also the NOTICE file.

Technical notes

• Model: EmbeddingGemma 300M (Google DeepMind), mixed-precision quantization (int4 embeddings/feed-forward/projection, int8 attention), for the LiteRT runtime.
• Signature embed_256: input text_batch int32 [1, 256] (token ids), output encodings float32 [1, 768].
• Input preparation (as in Google's official LiteRT sample): SentencePiece tokens, truncated to 254, BOS first, EOS last, padded with PAD to 256.
• Task prefixes from the official model card: task: search result | query: for queries, title: none | text: for documents.
• Output: 768 dimensions; Trama keeps the first 256 (Matryoshka) and re-normalizes them.