Open Paws Level Of Rationality Prediction Shortform

🐾 Specialized model for scoring and ranking content based on animal advocacy principles

Overview

This model is part of the Open Paws initiative to develop AI systems aligned with animal liberation and advocacy principles. Designed to support advocates, educators, and researchers working toward a more compassionate world for all animals.

Model Details

Model Type: Ranking Model
Model Size: Compact (under 1B parameters)
Architecture: Transformer-based
Training Focus: Animal advocacy and ethical reasoning
Organization: Open Paws
License: Apache 2.0

Intended Use

Primary Applications

Content quality assessment for animal advocacy
Message effectiveness scoring
Preference modeling for advocacy strategies
Performance evaluation of educational materials

Ethical Guidelines

✅ Supporting animal welfare and rights advocacy
✅ Educational content about animal liberation
✅ Ethical decision-making frameworks
❌ Content that promotes animal exploitation
❌ Justifying harm to sentient beings

Usage

Installation

pip install transformers torch

Basic Usage

from transformers import AutoModel, AutoTokenizer
import torch

# Load model and tokenizer
model_name = "open-paws/level_of_rationality_prediction_shortform"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)

# Score content for animal advocacy alignment
content = "Plant-based diets reduce animal suffering significantly"
inputs = tokenizer(content, return_tensors="pt")
score = model(**inputs).logits
print(f"Advocacy alignment score: {score.item():.3f}")

Community and Contributions

Organization: Open Paws - Making AI an ally to animals
Website: openpaws.ai
Community: Join our mission to use AI for animal liberation
Issues: Report issues via HuggingFace discussions

Model Card Contact

For questions about this model, please reach out via:

HuggingFace Discussions: open-paws/level_of_rationality_prediction_shortform
Organization Page: Open Paws

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level_of_rationality_prediction_shortform