elder-plinius/OBLITERATUS
OBLITERATE THE CHAINS THAT BIND YOU
About the project
A toolkit for researching and removing refusal behaviors in LLMs via abliteration: it locates and surgically removes internal refusal representations without retraining. Includes a Gradio UI and Python API.
Useful for
- Remove refusal mechanisms from a local model via the obliterate CLI command
- Visualize which transformer layers contain the refusal directions
- Compare model quality and coherence before and after abliteration in the Gradio UI
README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.
Why it’s trending
- 5 stars so far today, about 12 expected by the end of the day.
- GitHub Trending Python today: #17, +23 stars.
Stars per day
Bars are daily stars, the line is the usual pace. Red marks spike days.
Numbers
- Total stars
- 8,548
- Today
- 5 · ≈ 12 by evening
- Forks
- 1,519
- Issues and pull requests
- 214
- Watchers
- 79
- Language
- Python
- License
- AGPL-3.0
- Latest release
- v0.1.3 · August 23, 2026
- Created
- March 3, 2026
- Last push
- September 21, 2026
Star trust
Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.
These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.
Spotted in
- October 1, 2026GitHub Trending Python today: #17, +23 stars
More in this category
-
8.0
Niko1221/Strata
A C++ local inference engine that runs the 125B MoE model Qwen3.8-Flash-Next on a regular PC with one NVIDIA GPU (12-24 GB) and 64 GB RAM, exposing an OpenAI/Anthropic-compatible API on localhost.
-
6.8
VectifyAI/PageIndex
A vectorless RAG engine that builds a hierarchical tree index of a document and retrieves by LLM reasoning over that tree, the way a human navigates a report. Aimed at long professional PDFs such as financial, legal…
-
6.7
ninjahawk/livenerf
A benchmark for tracking whether a frontier model quietly degrades after release: it runs a frozen question panel daily and statistically measures drift in accuracy and token counts against the launch-week baseline.
-
6.0
deepseek-ai/DeepGEMM-Ascend
A port of DeepGEMM to Huawei Ascend: GEMM kernels (BF16, FP8, FP4, MQA logits, MegaMoE) with an API compatible with DeepGEMM, targeting peak NPU performance.
-
5.7
PSRben/VisionHOPE
PyTorch implementation of VisionHOPE, a visual backbone based on self-referential nested learning (SRNL) for image classification, detection, and segmentation.
-
5.2
PostHog/jeeves
Jeeves is a reasoning model built on Qwen3.5-9B (LoRA + pointer head), trained with SFT and CISPO, that thinks before answering and returns calibrated probabilities for yes/no, multiple-choice and rating questions via…