wokenlex/bubblecrawler-models

Gemma4E4B

gemma-4-E4B-it for the chunked engine of 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, 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. Use is also subject to the Gemma Prohibited Use Policy. See EmbeddingGemma/NOTICE.