Instructions to use soverius-ai/gemma-4-E4B-it-A2UI-Express-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use soverius-ai/gemma-4-E4B-it-A2UI-Express-LoRA with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download soverius-ai/gemma-4-E4B-it-A2UI-Express-LoRA --local-dir gemma-4-E4B-it-A2UI-Express-LoRA
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Gemma 4 E4B LoRA for A2UI Express (retrain 2026-11-07)
An mlx_lm-layout LoRA adapter (rank 8, scale 2.0, 342 logical matrices,
SHA-256 778467f51be80c125d41cecfc654f20083013e8602926f2ee1b7d7de910e105b)
trained with Unsloth for 160 steps on 240 conversations (the original 159 form
rows plus 90 informational cards) with the CopilotKit Express demo's system
prompt. Base: unsloth/gemma-4-E4B-it at
4e22d7e59e078e63a14f351efdc5232ed366b621; validation loss 0.038. Offline it
compiles 3 of the demo's 4 example prompts; it has not been exported for the
browser yet. Gemma weights keep Google's Gemma terms; see NOTICE.txt.
Hardware compatibility
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