Independent publisher
Richard Young
richardyoung
Large Language Models, LLM Evaluation, Instruction Following, Healthcare AI, Clinical AI,
Computational Neuroscience, Foundation Models, Responsible AI, AI Safety, Deep Learning,
Reinforcement Learning, NLP, MLOps, Neuroscience, Medical AI, Model Evaluation, Benchmark
Design, Open Science, Reproducible Research, Multi-Agent Systems
Models in Library1
Datasets in Library2
Models on Hugging Face77
Followers57
Compare the published evidence
This profile connects the 3 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.
Published tasks: Text generation.
Reported licenses: apache-2.0. Open a record to review its specific license and conditions.
Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.
Models
GGUF quantizations of richardyoung/Olmo-3-7B-Think-heretic, an abliterated build of allenai/Olmo-3-7B-Think (Ai2's fully open 7B reasoning model (open weights, data and training code) that thinks before answering) made with Heretic. The very low KL divergence (0.026, far below the 0.5 “damage” threshold) means the model retains essentially all of its original capabilities and coherence. Abliteration removes the "refusal direction" from a model's residual stream — a surgical modification that disables safety refusals without retraining. See Refusal in Language Models Is Mediated by a Single Direction. Heretic automates it: it searches ablation parameters with an optimizer (200 trials here)…
Open weights
apache-2.0
Datasets
Synthetic data only. Transcripts, word error rates by noise level, the draft notes and the sign-off checklist from one run of MIS 752 Lab 12.
Publicly accessible
Publicly accessible