Model Card for AI-URL-Shortener
Model Name: AI-URL-Shortener
Model Details
Model Description
AI-URL-Shortener is a machine learning model designed to automate the process of creating meaningful, human-readable URL shorteners. This model analyzes the original link provided by the user, generates a preview of the content, and suggests multiple unique and relevant suffix options for the shortened URL. The model is built to integrate seamlessly with URL shortener platforms, like LinksGPT, and aims to enhance user experience by providing smart suffix recommendations that align with the content of the original link.
Features:
- Original URL Analysis: Extract metadata such as title, description, and keywords.
- Dynamic Recommendations: Create suffixes based on the extracted metadata, user input, or custom branding.
- Intelligent Validation: Ensure generated suffixes are unique and valid.
Metadata:
- Developed by: LinksGPT Team
- Model type: LLM
- License: MIT
Model Sources
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
Uses
Intended Users:
- URL shortening platforms.
- Marketers looking for brand-aligned short links.
- Developers integrating custom URL shorteners into applications.
Direct Use
URL Shortening: Automatically generate short and descriptive URLs for social sharing or branding. Preview Links: Offer a content preview to help users select relevant suffixes for better engagement. Custom URL Recommendations: Provide personalized suggestions based on the content and user preferences.
Bias, Risks, and Limitations
Limitations:
- Content Preview Accuracy: The preview is dependent on the metadata availability of the original link.
- Suffix Creativity: The model generates suffixes within the constraints of URL standards, which may limit overly creative outputs.
- Real-Time Validation: Requires integration with a live URL shortener backend for uniqueness checks.
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.
How to Use:
- Input the original URL into the model.
- Receive a content preview and a list of recommended short-link suffixes.
- Select or customize a suffix based on the recommendations.
- Use the selected suffix to generate the final shortened URL via the backend system.
Example code snippet:
from transformers import pipeline
# Load model
model = pipeline("text-generation", model="huggingface/ai-url-shortener")
# Input original URL
original_url = "https://example.com/interesting-article"
# Generate suffix recommendations
results = model(f"Generate suffixes for: {original_url}")
print(results)
Training Details
Training Data
The model was trained on a large dataset of URLs, metadata, and user-selected short link patterns. The dataset includes a mix of general, e-commerce, social media, and enterprise links, ensuring versatility across industries.
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
The model is evaluated on:
- Suffix Relevance: How well the generated suffixes align with the link content.
- Uniqueness: Ensuring no duplicate or conflicting suffixes are generated.
- User Engagement: Improvement in click-through rates (CTR) for suggested short links.
Results
[More Information Needed]
Summary
Technical Specifications
Model Architecture and Objective
The model leverages a combination of:
- Natural Language Processing (NLP): To understand and extract relevant metadata from the original link.
- Transformer Models: For generating meaningful and creative suffix recommendations.
- Regex and Validation Layers: To ensure all generated suffixes conform to URL standards and avoid duplication.
Compute Infrastructure
Software
[More Information Needed]
More About LinksGPT
LinksGPT is a professional link management platform for custom short urls, brand building and conversion optimization. It offers intelligent URL shortening and expansion, custom domains, team roles, customizable QR codes, tracking and AI-based in-depth analytics, deep linking, openAPI and enhanced link security. Powered by AI, it provides intelligent insights and recommendations based on user behavior and click patterns, support data-driven brand strategies and marketing decisions.
Model Card Authors
LinksGPT