microsoft/SchGen_dataset
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How to use Ailiance-fr/SchGen-Qwen3.6-27B-EU-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir SchGen-Qwen3.6-27B-EU-MLX-4bit Ailiance-fr/SchGen-Qwen3.6-27B-EU-MLX-4bit
Apple-Silicon (MLX) 4bit quantization of
Ailiance-fr/SchGen-Qwen3.6-27B-EU,
a sovereign EU KiCad schematic-generation model (SchGen method,
Luo et al., 2026) by
ailiance.
MLX quantization, group_size=64, 4.5 bits per weight (~14 GB).
pip install mlx-lm
mlx_lm.generate --model Ailiance-fr/SchGen-Qwen3.6-27B-EU-MLX-4bit \
--prompt "Generate a schematic for an LM358 inverting amplifier, gain -10." \
--max-tokens 2048
from mlx_lm import load, generate
model, tok = load("Ailiance-fr/SchGen-Qwen3.6-27B-EU-MLX-4bit")
print(generate(model, tok, prompt="...", max_tokens=2048))
Served with enable_thinking=false. See the
full model card
for evaluation, limitations, and citation.
Apache-2.0. Derivative of Qwen/Qwen3.6-27B (Apache-2.0), trained on
microsoft/SchGen_dataset (MIT). See NOTICE.
4-bit