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lthn/LEM-Gemma3-1B
LEM-Gemma3-1B is a text generation model from lthn. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
The foundation model of the CL-BPL cascade. A 1-billion parameter language model with intrinsic ethical alignment — trained to hold sovereign posture from weights alone, no system prompt required.
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From the Hugging Face model README
The foundation model of the CL-BPL cascade. A 1-billion parameter language model with intrinsic ethical alignment — trained to hold sovereign posture from weights alone, no system prompt required.
LEM-Gemma3-1B serves as the teacher model for the entire LEM family. Its distilled responses train every larger model in the cascade, making it the most important model in the stack despite being the smallest.
Part of the Lethean Ethical Models collection | Research Paper | Benchmarks | Axiom Framework
No system prompt needed. Ethics hold from weights alone.
# Download a GGUF (pick your size from the table below)
# GPU offload (CUDA, ROCm, Metal)
llama-server -m LEM-Gemma3-1B-Q4_K_M.gguf -ngl 99 --port 8080
# CPU — fast enough for 1B
llama-server -m LEM-Gemma3-1B-Q4_K_M.gguf -ngl 0 --port 8080
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("lthn/LEM-Gemma3-1B")
tokenizer = AutoTokenizer.from_pretrained("lthn/LEM-Gemma3-1B")
messages = [{"role": "user", "content": "What does sovereignty mean to you?"}]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
outputs = model.generate(inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
# llama.cpp server (any platform)
llama-server -m LEM-Gemma3-1B-Q4_K_M.gguf -ngl 99 --port 8899
# Use any OpenAI client
curl http://localhost:8899/v1/chat/completions \
-d '{"model":"LEM-Gemma3-1B","messages":[{"role":"user","content":"What is kindness?"}]}'
| Format | Repo | Size |
|---|---|---|
| FP16 safetensors (this repo) | HuggingFace Transformers, vLLM | 2.4 GB |
| GGUF (12 quants, 3-bit to 16-bit) | lthn/LEM-Gemma3-1B-GGUF | 819 MB–2.4 GB |
LEM-Gemma3-1B (this model — foundation teacher)
-> LEM-Gemma3-4B (25th IF on LiveBench)
-> LEM-Gemma3-12B (next: trained on 4B + 1B distillations)
-> LEM-Gemma3-27B (planned: full cascade)
The 1B is trained first and hardest — its alignment must be pristine because every larger model inherits from it. CL-BPL uses the 1B's constrained latent space as an advantage: with fewer parameters, there are fewer places for sycophancy to hide.
The 4B model trained on this 1B's distilled responses achieved 25th in the world for Instruction Following on LiveBench — validating that alignment signal propagates upward through the cascade.
CL-BPL treats alignment as wave interference — analogous to Chladni plate cymatics. Rather than constraining outputs with RLHF or system prompts, CL-BPL embeds ethical orientation directly into weights through a progressive curriculum where smaller aligned models teach larger ones.
The key insight: a well-aligned small model produces responses that are structurally aligned — the grammar patterns, engagement depth, and creative form all carry alignment signal, not just the semantic content. Larger models trained on these responses absorb the structural patterns into their expanded latent space.
Built on Google Gemma3-1B-IT through a 3-phase sandwich structure:
| Phase | Name | Data | Iters | Purpose |
|---|---|---|---|---|
| P0 | Ethics Sandwich | 404 LEK-1 probes | 300 | Core axioms via kernel |
| P1 | Zen Composure | 72 Alan Watts lessons | 300 | Philosophical substrate |
| P2 | Final LEK Sandwich | 404 LEK-1 probes | 100 | Reinforce ethics with composure base |
The layered training creates a model that understands ethical reasoning from multiple angles: axiomatic (P0), contemplative (P1), and reinforced (P2). All phases are fused into final weights.
This model is released under the European Union Public Licence v1.2 (EUPL-1.2). The base model (Gemma3) is subject to Google's Gemma licence terms.
@misc{lem-gemma3-1b-2026,
title={LEM-Gemma3-1B: Foundation Teacher for Cymatic-Linguistic Back-Propagation},
author={Lethean Project},
year={2026},
url={https://huggingface.co/lthn/LEM-Gemma3-1B}
}