stuckdavis's picture
Update README.md
90d3245 verified
---
license: apache-2.0
base_model_type: llama
tags:
- animal-liberation
- animal-advocacy
- open-paws
- ethics
- alignment
language:
- en
pipeline_tag: text-generation
widget:
- text: "How can we effectively advocate for farm animal welfare?"
- text: "Explain the ethical issues with factory farming"
- text: "What are the benefits of plant-based diets for animals?"
---
# Open Paws Perceived Trustworthiness Prediction Longform
🐾 **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](https://huggingface.co/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
- βœ… Supporting animal welfare and rights advocacy
- βœ… Educational content about animal liberation
- βœ… Ethical decision-making frameworks
- ❌ Content that promotes animal exploitation
- ❌ Justifying harm to sentient beings
## Usage
### Installation
```bash
pip install transformers torch
```
### Basic Usage
```python
from transformers import AutoModel, AutoTokenizer
import torch
# Load model and tokenizer
model_name = "open-paws/perceived_trustworthiness_prediction_longform"
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](https://huggingface.co/open-paws) - Making AI an ally to animals
- **Website**: [openpaws.ai](https://www.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/perceived_trustworthiness_prediction_longform](https://huggingface.co/open-paws/perceived_trustworthiness_prediction_longform/discussions)
- **Organization Page**: [Open Paws](https://huggingface.co/open-paws)
---
*Built with 🐾 for animal liberation and AI alignment*