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Emmet-Allen/christAIn

sourceHugging Faceupdated 1y agoView on Hugging Face
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Model Card

ChristAI-uncensored

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Model Details

A Small Language Model trained on the King James Version of The Bible.

Model Description

<!-- Provide a longer summary of what this model is. --> 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.

  • —Developed by: Emmet Allen
  • —Model type: PEFT text-generation
  • —Language(s) (NLP): English
  • —License: MIT
  • —Finetuned from model [optional]: Qwen/Qwen2.5-0.5B-Instruct

Model Sources [optional]

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  • —Repository: (https://huggingface.co/Emmet-Allen/christAIn)

Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> Used to answer questions using the KJV bible as a reference point.

This is a Social Critique Project

Direct Use

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[More Information Needed]

Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Trained on the Christian Based KJV Bible. Heavily leans towards christian values and opinions.

Recommendations

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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

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https://huggingface.co/datasets/Emmet-Allen/The-Bible-KJV

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Training Procedure

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Will include Python Notebook.

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Environmental Impact

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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

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Compute Infrastructure

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Hardware

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Software

Void IDE Jupyter Notebook Nvidia-SMI Nvidia CUDA-Toolkit

Citation [optional]

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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

  • —PEFT 0.17.1