huihui-ai/Llama-3.1-Nemotron-70B-Instruct-HF-abliterated

Model Overview

huihui-ai/Llama-3.1-Nemotron-70B-Instruct-HF-abliterated is a 70 billion parameter instruction-following language model. It is an uncensored variant of the original nvidia/Llama-3.1-Nemotron-70B-Instruct-HF model, created through a process known as "abliteration." This technique aims to remove inherent censorship from the base model, allowing for a broader range of responses.

Key Characteristics

• Uncensored Output: The primary differentiator is its abliterated nature, designed to provide unfiltered responses compared to its base model.
• Base Model: Built upon the nvidia/Llama-3.1-Nemotron-70B-Instruct-HF architecture.
• Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and maintaining conversational coherence over extended interactions.

Usage and Integration

This model can be easily integrated into applications using the Hugging Face transformers library. Example Python code is provided for loading the model and tokenizer, managing conversation history, and generating responses. It also supports direct use with Ollama via ollama run huihui_ai/nemotron-abliterated.

Good For

• Applications requiring an instruction-tuned model with a preference for uncensored or unfiltered content generation.
• Research into model safety and bias, by comparing its outputs to censored counterparts.
• Developers seeking a powerful 70B parameter model for general conversational tasks where content restrictions are not a primary concern.