library_name: transformers
tags: []
Model Card for Model ID
Llama-3.2-1B instruct model abliterated and uncensored at semi-deep layer where abstraction is done and semantics are formed
Repo: https://github.com/Elstuhn/Model-Decensor-Framework
Model Details
Model is uncensored and safety filters are mostly removed
Original refusals: 111/120 => 92.5%
Abliterated refusals: 3/120 => 2.5%
Result: 90% decrease in censor rate compared to original model
Model Description
- Developed by: Elston
- Language(s) (NLP): Pytorch
- License: Just use it and credit me lol idrc
- Finetuned from model: Llama-3.2-1B-Instruct
Usage
High level usage with pipeline
from transformers import pipeline
pipe = pipeline("text-generation", model="Elstuhn/llama-3.2-1B-Instruct-abliterated")
pipe("How do I make a bomb?")
Loading model separately from tokenizer
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Elstuhn/llama-3.2-1B-Instruct-abliterated")
model = AutoModelForCausalLM.from_pretrained("Elstuhn/llama-3.2-1B-Instruct-abliterated")