I Created ErisForge, a Python Library for Abliteration of LLMs
ErisForge is a Python library designed to modify Large Language Models (LLMs) by applying transformations to their internal layers. Named after Eris, the goddess of strife and discord, ErisForge allows you to alter model behavior in a controlled manner, creating both ablated and augmented versions of LLMs that respond differently to specific types of input. It is also quite useful to perform studies on propaganda and bias in LLMs (planning to experiment with deepseek). Features - Modify internal layers of LLMs to produce altered behaviors. - Ablate or enhance model responses with the…
In plain words
ErisForge is a Python library that modifies Large Language Models by transforming their internal layers to alter model behavior in controlled ways. It enables researchers and developers to create ablated or augmented versions of LLMs that respond differently to specific inputs, useful for studying propaganda and bias. The library includes tools to modify layers, enhance or suppress responses, measure refusal expressions, and apply custom behavior transformations.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
ErisForge is a Python library designed to modify Large Language Models (LLMs) by applying transformations to their internal layers. Named after Eris, the goddess of strife and discord, ErisForge allows you to alter model behavior in a controlled manner, creating both ablated and augmented versions of LLMs that respond differently to specific types of input. It is also quite useful to perform studies on propaganda and bias in LLMs (planning to experiment with deepseek). Features - Modify internal layers of LLMs to produce altered behaviors. - Ablate or enhance model responses with the AblationDecoderLayer and AdditionDecoderLayer classes. - Measure refusal expressions in model responses using the ExpressionRefusalScorer. - Supports custom behavior directions for applying specific types of transformations.
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