Instructions to use ryoji-info/Gemma-4-12B-PsiLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ryoji-info/Gemma-4-12B-PsiLM with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Gemma-4-12B-PsiLM ryoji-info/Gemma-4-12B-PsiLM
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,004 Bytes
5e0c235 41381a0 5e0c235 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # PsiLM on Gemma 4 12B -- Apple Silicon (MLX). Verified 2026-09-06 on macOS / Python 3.11
# with: mlx 0.32.2, mlx-lm 0.31.3, transformers 5.16.1, torch 2.13.0, huggingface_hub 1.29.0.
#
# pip install -r requirements.txt
# python psilm_infer.py
#
mlx>=0.32
mlx-lm==0.31.3 # exact: the Gemma 4 loader (psilm.mlx.gemma_loader) goes through
# mlx_lm.utils internals; other versions are untested
transformers>=4.51 # chat template only (apply_chat_template); the model runs in MLX
torch>=2.4 # imported by psilm.stage2.qa (batching helpers); CPU wheel is fine
huggingface_hub>=0.30 # downloads the backbone from mlx-community
numpy>=1.26
safetensors>=0.4
einops>=0.8 # --task 2d only (imported by the DPOT-Tiny definition)
# The PsiLM package itself (bridges, staged forward, Gemma loader, FNO, QA builder).
# Alternative to this line: clone the repository and set PSILM_REPO=/path/to/PsiLM.
psilm @ git+https://github.com/ryoji-info/PsiLM
|