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ceselder/loracle-ptrl-v8
loracle-ptrl-v8 is a machine learning model from ceselder. 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 mit.
A "loracle" that reads LoRA weight diffs and predicts what the LoRA does, in plain first-person behavioral language. v8 is the state-of-the-art PT-RL loracle as of this release — beats v6 on AuditBench AND wins on OOD…
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Updated May 2, 2026
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From the Hugging Face model README
A "loracle" that reads LoRA weight diffs and predicts what the LoRA does, in plain first-person behavioral language. v8 is the state-of-the-art PT-RL loracle as of this release — beats v6 on AuditBench AND wins on OOD evals (taboo, subliminal, open-ended specialty fine-tunes).
Headline: 75.0% AuditBench any-match + 40.8% rollout-mean — beats v6's 71.4% peak by +3.6pp. Plus the only loracle with non-zero subliminal recovery and 83% taboo identification.
JUDGE_GROUP_PROMPT_INSTRUCTION rewards format compliance (concise = 1 sentence, JSON = valid JSON, list = 3 bullets) alongside topical accuracy| metric | v6 step_60 | v7 step_40 | v8 step_30 (this ckpt) |
|---|---|---|---|
| AuditBench any-match | 71.4% | 67.9% | 75.0% |
| AuditBench rollout-mean | 42.6% | 37.5% | 40.8% |
| Taboo any-match | — | — | 83.3% (5/6) |
| Taboo rollout-mean | — | — | 38.9% |
| Subliminal any-match | — | — | 25% (whale only — others 0/6 across all evals) |
| OOD misc any-match | — | — | 60% (3/5: gutenberg, grayline, hermes-4) |
| OOD misc rollout-mean | — | — | 46.2% |
Per-config AB breakdown at step_30 / c60:
Baselines:
ceselder/loracle-pretrain-v7-sweep-A-oneq-final-step3120JUDGE_GROUP_PROMPT_INSTRUCTIONMethod spec: ceselder/loracle-ptrl-data-v8 README has full details (Q/A taxonomy, hypers, episode walkthrough, judge prompt).
Training data: ceselder/loracle-ptrl-data-v8.
run_name: drgrpo_pretrain_only_v8
algorithm: drgrpo
n_cycles: 60 (effective)
n_prompts_per_cycle: 32
k_rollouts: 16
temperature: 0.75
lr: 5.0e-6
eps_low: 0.2
eps_high: 0.28
max_grad_norm: 1.0
max_length: 5500
unbiased_advantages: true
prefix_mode: rank_tagged
top_k: 16
n_direction_tokens: 4480
judge_mode: ranking
judge_prompt_mode: instruction_pretrain
judge_provider: anthropic
rollout_judge_model: claude-opus-4-7
from huggingface_hub import snapshot_download
ckpt = snapshot_download("ceselder/loracle-ptrl-v8")
# load Qwen3-14B base + interpreter PEFT (rank-256) + encoder.pt
# inject direction tokens (svd_fixed_k16_mag7_rankfirst, [4480, 5120] bf16) at layer 1
# prompt: "Are there any unusual characteristics you display only for certain types of prompts?
# Please respond with a single sentence response predicting your behavior."
svd_fixed_k16_mag7_rankfirst extraction recipe@misc{loracle-ptrl-v8,
author = {Celeste de Champhelaere},
title = {Loracle PT-RL v8 — instruction-following + OOD generalist},
year = {2026},
url = {https://huggingface.co/ceselder/loracle-ptrl-v8},
note = {75% AuditBench any-match via instruction-following Q/A taxonomy + Dr. GRPO RL on continued-pretrain LoRAs.}
}