CoolFace
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varocarras/Humaneyes

sourceHugging Facemitupdated 11mo agoView on Hugging Face
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Model Card

Humaneyes

Model Description

Humaneyes is an advanced text transformation model designed to convert AI-generated text into more human-like content and provide robust defense against AI content detection trackers. The model leverages sophisticated natural language processing techniques to humanize machine-generated text, making it indistinguishable from human-written content.

Model Details

  • —Developed by: Eemansleepdeprived
  • —Model type: AI-to-Human Text Transformation
  • —Primary Functionality:
  • —AI-generated text humanization
  • —AI tracker defense
  • —Language(s): English
  • —Base Architecture: Pegasus Transformer
  • —Input format: AI-generated text
  • —Output format: Humanized, natural-sounding text

Key Capabilities

  • —Transforms AI-generated text to sound more natural and human-like
  • —Defeats AI content detection algorithms
  • —Preserves original semantic meaning
  • —Maintains coherent paragraph structure
  • —Introduces human-like linguistic variations

Intended Use Cases

  • —Academic writing assistance
  • —Content creation and disguising AI-generated content
  • —Protecting writers from AI content detection systems
  • —Enhancing AI-generated text for more authentic communication

Ethical Considerations

  • —Intended for creative and protective purposes
  • —Users should respect academic and professional integrity
  • —Encourages responsible use of AI-generated content
  • —Not designed to facilitate academic dishonesty

Technical Approach

Humanization Strategies

  • —Natural language variation
  • —Contextual rephrasing
  • —Introducing human-like imperfections
  • —Semantic preservation
  • —Stylistic diversification

Anti-Detection Techniques

  • —Defeating AI content trackers
  • —Randomizing linguistic patterns
  • —Simulating human writing nuances
  • —Breaking predictable AI generation signatures

Performance Characteristics

  • —High semantic similarity to original text
  • —Reduced AI detection probability
  • —Contextually appropriate transformations
  • —Minimal loss of original meaning

Limitations

  • —Performance may vary based on input text complexity
  • —Not guaranteed to bypass all AI detection systems
  • —Potential subtle semantic shifts
  • —Effectiveness depends on input text characteristics

Usage Example

python
from transformers import PegasusTokenizer, PegasusForConditionalGeneration

tokenizer = PegasusTokenizer.from_pretrained('Eemansleepdeprived/Humaneyes')
model = PegasusForConditionalGeneration.from_pretrained('Eemansleepdeprived/Humaneyes')

ai_generated_text = "Your AI-generated text goes here."
inputs = tokenizer(ai_generated_text, return_tensors="pt")
outputs = model.generate(**inputs)
humanized_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

Contact and Collaboration

For inquiries, feedback, or collaboration opportunities, contact:

  • —Email: eeman.majumder@gmail.com

License

Released under the MIT License

Disclaimer

Users are responsible for ethical use of the Humaneyes Text Humanizer. Respect academic and professional guidelines.