Wizard L M 7 B Uncensored

Introduction

WizardLM-7B-Uncensored is a language model trained to be free of built-in alignment or moralizing constraints, allowing for flexibility in alignment customization through methods like Reinforcement Learning from Human Feedback (RLHF) with Low-Rank Adaptation (LoRA). It uses a subset of the WizardLM-alpaca-evol-instruct-70k-unfiltered dataset, ensuring that responses are not pre-aligned with specific moral frameworks.

Architecture

The model is developed using the Transformers library and is implemented in PyTorch. It is designed for text generation tasks and is compatible with text-generation-inference and inference endpoints, facilitating deployment in various applications.

Training

The training process involved filtering the dataset to exclude responses with alignment or moralizing content. This approach aims to produce an uncensored model that can be further aligned according to user needs using additional training techniques like RLHF.

Guide: Running Locally

1. Environment Setup: Ensure you have a compatible environment with PyTorch and Transformers installed.
2. Download the Model: Access the model files from the Hugging Face repository.
3. Load the Model: Use the Transformers library to load the model into your application.
4. Run Inference: Implement your text generation logic using the model.
5. Cloud GPUs: For optimal performance, consider using cloud services that offer GPU support, such as AWS, Google Cloud, or Azure.

License

The model is distributed under an "other" license. Users are advised to review the specific licensing terms provided within the model's repository. Users are responsible for the content generated and its subsequent publication, analogous to the responsibility one holds when using potentially dangerous objects.