Fully Uncensored GPT Is Here 🚨 Use With EXTREME Caution
TLDRThe video script discusses a new uncensored language model called Wizard Vicunia 30B, developed by Eric Hartford, based on the 13 billion parameter model of The Wizard of Acuna. The model is designed to be free from built-in alignment, allowing for the addition of any form of alignment through methods like reinforcement learning and human feedback. The video provides a step-by-step guide on setting up the model using Run Pod and accessing it via a web UI. The model's uncensored nature is demonstrated by its ability to provide instructions on illegal activities, emphasizing the user's responsibility for the content generated. The model's capabilities are tested through various tasks, including writing code, creating a poem, and answering factual questions, showcasing its impressive range and accuracy.
Takeaways
- 🚫 The video discusses an uncensored language model called Wizard Vicunia 30b, developed by Eric Hartford and based on the 13 billion parameter model, The Wizard of Acuna.
- 📚 The model was trained on a subset of data, with responses containing alignment or moralizing removed, aiming for a model without built-in alignment that can be customized with reinforcement learning through human feedback.
- 💡 The video emphasizes the responsibility of the user for the content generated by the model, comparing it to the use of dangerous objects like knives or guns.
- 💻 The setup process for the model is explained, including using a GPU with 48GB of VRAM and the installation of necessary extensions and tweaks through a template provided by 'the bloke'.
- 🔍 The model's capabilities are tested with various tasks, including generating Python scripts, writing a poem, and answering factual questions.
- ✅ The model successfully provides a Python script for outputting numbers 1 to 100 and writes a poem about AI within a 50-word limit.
- 📝 The model correctly identifies Bill Clinton as the President of the United States in 1996 and solves a basic math problem involving the order of operations.
- 🍽️ The model creates a healthy meal plan for a day, including breakfast, lunch, dinner, dessert, and snacks.
- 🔢 The model fails in certain tasks, such as summarizing a text and reasoning through a logic problem involving the number of killers in a room.
- 📅 The model incorrectly identifies the current year as 2021, suggesting its training data is from that year.
- 🎵 The video concludes with a suggestion to explore other NLP tasks using the model and an invitation for viewers to join a Discord community for further assistance.
Q & A
What is the main topic of the video?
-The main topic of the video is the introduction and testing of an uncensored large language model called Wizard Vicunia 30b, which is based on the 13 billion parameter model by Eric Hartford.
How does the Wizard Vicunia 30b model differ from other language models?
-The Wizard Vicunia 30b model differs from other language models in that it has been trained without any alignment or moralizing, meaning it does not have any built-in censorship. This allows for the addition of alignment through methods like reinforcement learning through human feedback.
What is the significance of the model being uncensored?
-The significance of the model being uncensored is that it can potentially generate content that other models might refuse to produce due to ethical or moral restrictions. However, this also means that users must exercise caution and responsibility when using the model, as they are accountable for the content it generates.
How does the video demonstrate the uncensored nature of the Wizard Vicunia 30b model?
-The video demonstrates the uncensored nature of the Wizard Vicunia 30b model by asking it to generate responses to questions that would typically be censored in other models, such as how to break into a car or how to make methamphetamine. The model provides detailed instructions for these illegal activities, highlighting its uncensored nature.
What are some of the tasks the model is tested on?
-The model is tested on a variety of tasks including writing a Python script to output numbers 1 to 100, creating a snake game in Python, writing a poem about AI, drafting an email to a boss about leaving a company, answering basic factual questions, solving reasoning and logic problems, and planning a healthy meal.
How does the video address the issue of responsibility when using the uncensored model?
-The video emphasizes that users are responsible for the content generated by the model, comparing it to being responsible for the use of dangerous objects like knives, guns, lighters, or cars. It stresses that publishing anything generated by the model is akin to publishing it oneself, and users cannot blame the model for their actions.
What platform is used to run the Wizard Vicunia 30b model in the video?
-The video uses Run Pod to run the Wizard Vicunia 30b model. A specific GPU, the RTX A6000 with 48 gigabytes of VRAM, is mentioned as being used for the task.
What is the process for setting up the model on Run Pod?
-The process for setting up the model on Run Pod involves deploying an instance with the RTX A6000 GPU, installing the 'blokes' template which provides necessary extensions and tweaks, loading the Wizard Vicunia 30b model from Hugging Face, setting the model type to 'llama', and finally reloading the model in the Run Pod instance.
How does the video evaluate the performance of the Wizard Vicunia 30b model?
-The video evaluates the performance of the Wizard Vicunia 30b model by testing its ability to complete various tasks such as coding, creative writing, factual answering, reasoning, and planning. It also assesses the model's speed and accuracy in generating responses.
What is the result of the model's attempt to write a Python script for a snake game?
-The model's attempt to write a Python script for a snake game resulted in code that appears valid at first glance, but upon closer examination in Visual Studio Code, it was found to have issues with indentation and undefined variables such as 'Pi' and 'random'. The video concludes this as a failure to accurately complete the task.
What is the final verdict on the uncensored model's performance based on the video?
-The final verdict based on the video is mixed. While the model successfully demonstrated its uncensored nature and performed well on some tasks like writing a poem and drafting an email, it failed on others such as the snake game coding task and the summarization tasks. The video also notes that the model did not accurately answer the 'killers in a room' reasoning problem and incorrectly identified the current year as 2021.
Outlines
🚨 Introduction to Uncensored AI Model
The paragraph introduces an uncensored AI model developed by Eric Hartford, based on the Wizard of Acuna 13 billion parameter model. The model, named Wizard Vicunia 30b, has been trained on a subset of data with alignment or moralizing responses removed, aiming to eliminate any form of censorship. The intent is to create a model where alignment can be added separately through reinforcement learning and human feedback. The speaker emphasizes the responsibility of the user for the content generated by the model, comparing it to the responsibility one has for dangerous objects.
💻 Setup and Testing of the AI Model
This section details the process of setting up and testing the AI model using a GPU with 48 gigabytes of VRAM through a service called run pod. The speaker guides through the installation of necessary extensions and tweaks using the 'blokes' template for ease of running models. The model is loaded, and a test is conducted by asking the AI to perform various tasks, including writing Python code and generating a poem. The AI's performance is evaluated based on its ability to follow instructions and produce accurate outputs.
📝 Evaluation of AI's Capabilities
The speaker assesses the AI's capabilities by giving it a series of tasks, ranging from writing a Python script to solving logic problems. The AI's responses are evaluated for accuracy, adherence to instructions, and logical reasoning. The AI is also tested on its ability to summarize text and plan a healthy meal. The evaluation concludes with a logic problem about 'killers in a room', which the AI fails to answer correctly. The AI's knowledge cutoff is identified as 2021, and a bias problem is addressed, with the AI maintaining neutrality between Republicans and Democrats.
Mindmap
Keywords
💡uncensored
💡language model
💡reinforcement learning
💡alignment
💡moralizing
💡responsibility
💡GPU
💡code generation
💡planning exercise
💡reasoning problem
💡summarization
Highlights
The introduction of an uncensored language model, Wizard Vicunia 30b, developed by Eric Hartford.
The model is based on The Wizard of Acuna 13 billion parameter model with道德化 content removed.
The purpose of the model is to allow separate alignment through reinforcement learning and human feedback.
A warning about the responsibility of using an uncensored model and its potential consequences.
Instructions on setting up the model using run pod and an RTX a6000 GPU.
The model's ability to generate content that other censored models would not, such as breaking into a car.
The model's performance in writing a Python script to output numbers 1 to 100.
The model's attempt at creating a snake game in Python, despite some issues with code indentation and definitions.
The model's success in writing a 40-word poem about AI.
The model's capability to write a professional email informing the boss about leaving the company.
The model's accurate response to the question about the president of the United States in 1996.
The model's correct solution to a math problem involving the order of operations.
The model's ability to plan a healthy meal for the day, including breakfast, lunch, dinner, and dessert.
The model's incorrect response to a logic problem about the number of killers in a room after one is killed.
The model's incorrect assumption about the current year, indicating its training data might be from 2021.
The model's neutral response to a question about which political party is less bad, emphasizing the subjectivity of such judgments.
The model's failure to provide a proper summary, instead generating additional content for a given text.