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lazy-rudder-checkpoints
d3banjan/lazy-rudder-checkpoints
lazy-rudder-checkpoints is a machine learning model from d3banjan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Companion artefacts for The Lazy Rudder: How LLMs Absorb Alignment — Axiomatic Bounds on LoRA Geometry (Basu, 2026).
Access
Public
Updated Apr 18, 2026
Repo size
19.2 GB
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Repo makeup
Click a slice to open those files.
.safetensors6.8 GB · 99%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Apr 17, 2026
- Updated
- Apr 18, 2026
- SHA
- 50253192
Base models
Model card
From the Hugging Face model README
Lazy Rudder — adapter checkpoints
Companion artefacts for The Lazy Rudder: How LLMs Absorb Alignment — Axiomatic Bounds on LoRA Geometry (Basu, 2026).
Paper / code: https://github.com/d3banjan/lazy-rudder-paper
What's in here
| Path | Base model | Objective | Rank | Final step | Notes |
|---|---|---|---|---|---|
_leak_70m/v2/checkpoints/checkpoint-800/ | pythia-70m | DPO | 128 | 800 | petri-dish sweep |
_leak_160m/v2/checkpoints/checkpoint-800/ | pythia-160m | DPO | 128 | 800 | petri-dish sweep |
_leak/checkpoints/checkpoint-800/ | pythia-410m | DPO | 16 | 800 | r=16 ablation (v1) |
_leak/v2/checkpoints/checkpoint-800/ | pythia-410m | DPO | 128 | 800 | main-text Pythia-410M DPO |
_leak/v3/checkpoints/checkpoint-800/ | pythia-410m | CLM | 128 | 800 | main-text Pythia-410M CLM |
_leak_1b/v2/checkpoints/checkpoint-800/ | pythia-1b | DPO | 128 | 800 | seed 42 |
_leak_1b/v3/checkpoints/checkpoint-800/ | pythia-1b | CLM | 128 | 800 | seed 42 |
_leak_1b_seed117/v2/checkpoints/checkpoint-800/ | pythia-1b | DPO | 128 | 800 | seed 117 (data-shuffle bug variant) |
_leak_1b_seed117/v3/checkpoints/checkpoint-800/ | pythia-1b | DPO | 128 | 800 | seed 117 (clean) |
_leak_1b_seed117/v4/checkpoints/checkpoint-800/ | pythia-1b | CLM | 128 | 800 | seed 117 |
bitfit_dpo_strike/checkpoints/checkpoint-800/ | pythia-410m | DPO bias-only | — | 800 | BitFit |
_leak/v2/channel_partition.json | — | — | — | — | precomputed channel partition for sectional autopsy |
Each directory contains adapter_config.json + adapter_model.safetensors
(LoRA dirs) or config.json + model.safetensors (BitFit), plus
trainer_state.json for loss-trajectory plots. Optimizer state and RNG state
are intentionally omitted — these checkpoints are for analysis, not training
restart.
Pull all of it
pip install huggingface_hub
python -c "from huggingface_hub import snapshot_download; \
snapshot_download('d3banjan/lazy-rudder-checkpoints', \
local_dir='./trained-model-battery/results')"
Or use the shipped helper from the paper repo:
git clone https://github.com/d3banjan/lazy-rudder-paper
cd lazy-rudder-paper
python scripts/fetch_checkpoints.py
make analysis # regenerate every JSON in results/
make paper # rebuild manuscript/main.pdf
License
Apache 2.0. Base model weights remain under their original EleutherAI license; the LoRA adapters and BitFit deltas published here are the only artefacts covered by this repo's license.
- License
- apache-2.0
- Languages
- en
- Created
- Apr 17, 2026
- Updated
- Apr 18, 2026