---
license: other
license_name: apache-2.0-and-gemma
license_link: LICENSE.md
base_model:
- google/gemma-4-E4B-it
- google/embeddinggemma-300m
tags:
- coreml
- apple-neural-engine
- on-device
---

## Gemma4E4B

gemma-4-E4B-it for the chunked engine of
[john-rocky/CoreML-LLM](https://github.com/john-rocky/CoreML-LLM): four decode
chunks plus batched prefill (N = 2048), context 4096.

This conversion differs from `mlboydaisuke/gemma-4-E4B-coreml` in three ways:

- **RoPE tables fixed.** `cos_full.npy` / `sin_full.npy` implement Gemma 4's
  proportional RoPE for full attention: only the first 64 of the 256
  frequencies rotate. Upstream rotates all of them, so the model loses track of
  anything more than ~512 tokens back.
- **Band mask for prefill.** Prefill applies the 512-token band mask to the
  sliding-window layers.
- **Multifunction chunks.** Each `chunkN.mlmodelc` holds two functions,
  `decode_q1` (the default) and `prefill`, which share one copy of the weights.
  The `verify_qK` functions are not included.

The tokenizer adds no BOS token, so prepend `<bos>` yourself.

## EmbeddingGemma

EmbeddingGemma-300M from
[erjigit17/embeddinggemma-300m-ane-coreml](https://huggingface.co/erjigit17/embeddinggemma-300m-ane-coreml),
compiled to `model.mlmodelc`.

- Inputs: `input_ids` and `attention_mask`, each int32 `[1, 128]`.
- Output: `embedding`, `[1, 768]`.

## Licenses

- **Gemma4E4B:** Apache 2.0, the license of `google/gemma-4-E4B-it`.
- **EmbeddingGemma:** Gemma is provided under and subject to the Gemma Terms of
  Use found at [ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms).
  Use is also subject to the
  [Gemma Prohibited Use Policy](https://ai.google.dev/gemma/prohibited_use_policy).
  See `EmbeddingGemma/NOTICE`.