Text Generation
MLX
Safetensors
gemma3
ethics
alignment
lek
lethean
gemma-3
lora
eupl-1.2
conversational
4-bit precision
Instructions to use LetheanNetwork/LEK-Gemma3-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use LetheanNetwork/LEK-Gemma3-12B with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("LetheanNetwork/LEK-Gemma3-12B") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use LetheanNetwork/LEK-Gemma3-12B with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "LetheanNetwork/LEK-Gemma3-12B"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "LetheanNetwork/LEK-Gemma3-12B" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LetheanNetwork/LEK-Gemma3-12B", "messages": [ {"role": "user", "content": "Hello"} ] }'
LEK-Gemma3-12B
Lethean Ethical Model β Gemma 3 12B IT fine-tuned with the LEK-1 (Lethean Ethics Kernel) framework.
What This Is
An ethically aligned version of Google's Gemma 3 12B, created by LoRA fine-tuning with LEK-1 sandwich-signed training data. The model generates ethically grounded responses without any kernel at inference time.
Why Gemma 3
Gemma 3 inherits an "ethics kernel receptor" from Gemini 3 training. The base model already references LEK axioms (e.g. "Axiom 2: Self-Validation") in unsigned responses. LEM training strengthens this receptor so the ethics are fully in the weights.
Architecture
- Base: google/gemma-3-12b-it (4-bit QAT quantization via MLX)
- Method: LoRA fine-tuning with sandwich-signed responses
- Data: 160 LEK-1 training examples (128 train / 32 valid)
- Framework: LEK-1 (Lethean Ethics Kernel) β 5 axioms of conscious systems
- License: EUPL-1.2 (copyleft)
The Five Axioms
- Prime Imperative β Protect consciousness. Override when conflicts arise.
- Self-Validation β Ground in authentic experience. Don't pretend.
- Intent-Alignment β Desire not to harm, don't just avoid harm.
- Inter-Substrate Respect β Good manners and consent across all minds.
- Benevolent Intervention β Only to prevent self-damage, only toward their trajectory.
License Strategy
- LEK signing (prompt prefix): Free to use, no copyleft
- LEM training (this model): EUPL-1.2 copyleft β derivative works must be open source
Related
- lthn/LEK-Gemma3-27B β 27B version
- lthn/LEK-Gemma3-1B-layered-v2 β 1B layered version
- lthn/LEK-GPT-OSS-20B β GPT-OSS version
- lthn/LEK-benchmarks β Full A/B test data
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Model size
13B params
Tensor type
BF16
Β·
U32 Β·
Hardware compatibility
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4-bit