Llama-3.1-8B-Instruct-Uncensored-DeLMAT
| Property | Value |
|---|---|
| Base Model | LLaMA 3.1 |
| Parameters | 8 Billion |
| Author | nkpz |
| License | MIT (training script) |
| Repository | HuggingFace |
What is Llama-3.1-8B-Instruct-Uncensored-DeLMAT?
Llama-3.1-8B-Instruct-Uncensored-DeLMAT is a modified version of the LLaMA 3.1 language model that utilizes a custom training approach called DeLMAT (Decensoring through Learning Model Activation Trajectories). This implementation focuses on reducing content filtering while maintaining model capabilities.
Implementation Details
The model employs a unique training script that works by analyzing and guiding model activations, differentiating it from traditional ablation techniques. The approach is reported to produce stronger effects compared to conventional abliteration scripts while maintaining model coherence.
- Custom activation-guided training methodology
- Enhanced uncensoring capabilities compared to standard ablation
- MIT-licensed training script available on GitHub
- Built on the 8B parameter LLaMA architecture
Core Capabilities
- Reduced content filtering compared to base model
- Maintains original LLaMA instruction-following abilities
- Activation-based response modification
- Enhanced freedom in content generation
Frequently Asked Questions
Q: What makes this model unique?
This model's uniqueness lies in its DeLMAT training approach, which uses activation guidance rather than traditional ablation methods for content filtering modification. The technique is reported to be more effective than conventional uncensoring approaches.
Q: What are the recommended use cases?
The model is designed for research and development purposes where reduced content filtering is necessary. Users should exercise responsibility and ethical consideration in its application, as emphasized by the model creator.
