ChristAI-uncensored
Model Details
A Small Language Model trained on the King James Version of The Bible.
Model Description
Created as a critque peoples usage of AI specifically LLMs/SLMs
as a confidant, therapist, and in some cases a new god (think American Gods by Neil Gaiman).
This has lead to cases of people creating AI-centered cults, rash decision making as suggested by AI,
and in a praticular case that sparked the intrest of the creation of this model, a 16 year old boy
commiting
suicide as suggested by ChatGPT.
This model is the uncensored model, which is able to better answer more nuanced questions that pertain to
The Bible and how it pertains to the world.
The model does not hold back.
- Developed by: Emmet Allen
- Model type: PEFT text-generation
- Language(s) (NLP): English
- License: MIT
- Finetuned from model [optional]: dphn/Dolphin3.0-Qwen2.5-0.5B
Model Sources [optional]
Uses
Used to answer questions using the KJV bible as a reference point.
This is a Social Critique Project
Direct Use
[More Information Needed]
Downstream Use [optional]
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
Trained on the Christian Based KJV Bible.
Heavily leans towards christian values and opinions.
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Training Details
Training Data
[More Information Needed]
Training Procedure
Will include Python Notebook.
[More Information Needed]
Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
- Hardware Type: NVidia 3070ti 8GB VRAM
- Hours used: < 1hr
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Compute Infrastructure
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Hardware
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Software
Void IDE
Jupyter Notebook
Nvidia-SMI
Nvidia CUDA-Toolkit
Citation [optional]
BibTeX:
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APA:
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Glossary [optional]
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More Information [optional]
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Model Card Authors [optional]
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Model Card Contact
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Framework versions
