by Extraltodeus · LLM 插件 · ★ 228
J-Wash Reshape a model's identity and behavior by editing token directions, then bake those edits into a real checkpoint you can run anywhere. No training, no dataset, no fine-tuning. J-Wash is a local studio (FastAPI + React) for exploring and editing the J-space of any Hugging Face decoder LLM. You chat with a model while a live Jacobian lens shows what each layer is "reading," pin and inspect concepts, then wash the model's identity or behavior with a few token-level rules — turn "I am a large language model" into "I am a large language fish" — and export the result as a standalone model...
| Stars | 228 |
| Forks | 25 |
| Language | Python |
| Category | LLM 插件 |
| License | Apache-2.0 |
| Quality Score | 69.4425312827607/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-06 |
| Created | 2026-07-13 |
| Platforms | python |
| Est. Tokens | ~16k |
Explore other popular llm 插件 tools:
J-Wash is Jacobian-Brainwash : A manual alignment tool for large language models built on Anthropic's Jacobian Lens. Results are exportable.. It is categorized as a LLM 插件 with 228 GitHub stars.
J-Wash is primarily written in Python. It covers topics such as abliteration, ai, anthropic.
You can find installation instructions and usage details in the J-Wash GitHub repository at github.com/Extraltodeus/J-Wash. The project has 228 stars and 25 forks, indicating an active community.
J-Wash is released under the Apache-2.0 license, making it free to use and modify according to the license terms.