Classify patent abstracts into subsectors
fake news detection using distilbert trained on liar dataset
Explore BERT model interactions
Calculate patentability score from application
Classify text into categories
List the capabilities of various AI models
Rerank documents based on a query
Identify named entities in text
This is for learning purpose, don't take it seriously :)
Type an idea, get related quotes from historic figures
Similarity
Generate Shark Tank India Analysis
Extract... key phrases from text
The Zero Shot Patent Classifier is an advanced AI-powered tool designed for Text Analysis. It specializes in classifying patent abstracts into specific subsectors with high accuracy. Leveraging cutting-edge Natural Language Processing (NLP) models, it enables users to efficiently organize and categorize patent documents without prior training on specific datasets.
• Automatic Classification: Instantly categorize patent abstracts into predefined subsectors.
• High Accuracy: Utilizes state-of-the-art language models for precise classification.
• Customizable Subsectors: Supports classification into user-defined categories.
• Efficient Processing: Handles large volumes of patent abstracts quickly.
• Integration-Friendly: Easily integrates with existing patent management systems.
• User-Friendly Interface: Simple input and output format for seamless usage.
What is the accuracy of Zero Shot Patent Classifier?
The accuracy depends on the quality of the input abstract and the complexity of the subsectors but typically achieves high precision.
Can I customize the subsectors for classification?
Yes, the tool allows users to define custom subsectors for tailored classification needs.
How do I format the input for the classifier?
Input should be a plain text string of the patent abstract, free of markdown or special formatting.