gemma4-e2b-Snowfox-hf

Gemma 4 E2B SnowFox (canonical BF16 source)

This is the canonical merged BF16 Transformers checkpoint of SnowFox — a language-only LoRA merge built on Google's Gemma 4 E2B instruction QAT-derived model. Every SnowFox distribution (MLX FP16, MLX 4-bit, MLX 6-bit, GGUF) is derived from this repository, so this is the package to use for full-precision Transformers inference or as the source for your own exports.

SnowFox is trained by Michael Anthony Falabella.

What SnowFox is

SnowFox is a language-only LoRA merge: the image and audio towers were frozen during fine-tuning and are retained unchanged from the base model. Only the language backbone received the SnowFox LoRA adaptation. The base is Google's QAT-derived q4_0-unquantized checkpoint, which carries clipping parameters on the multimodal towers that are preserved here.

Model size

Note: Hugging Face's model page may report a smaller "params" figure for the quantized MLX derivatives of this model. That is a display artifact — those repos store weights as packed uint32 words (8× 4-bit / 5× 6-bit values per word) and HF counts each packed word as one parameter. The true count is unchanged (~5.1B total / ~2.3B effective).

Exact lineage

• Base: google/gemma-4-E2B-it-qat-q4_0-unquantized
• Pinned base revision: 6befbaca7398925921802abd1f277b495b78b738
• Method: LoRA fine-tune (language-only), merged into the base model
• Claim boundary: QAT-derived from the base; SnowFox's post-LoRA weights were not newly QAT-calibrated.

Quick start

from transformers import AutoModelForCausalLM, AutoProcessor

model_id = "MichaelAnthony/gemma4-e2b-Snowfox-hf"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto",
)

Derivative packages

License

Gemma 4 is Apache-2.0. This derivative package uses the Apache-2.0 license declared by the pinned base model. See LICENSE and NOTICE.md for the lineage and modification notice.