Deduplicate HuggingFace datasets in seconds
Find the best matching text for a query
Upload a PDF or TXT, ask questions about it
Retrieve news articles based on a query
Generative Tasks Evaluation of Arabic LLMs
Give URL get details about the company
Parse and highlight entities in an email thread
ModernBERT for reasoning and zero-shot classification
Easily visualize tokens for any diffusion model.
Open LLM(CohereForAI/c4ai-command-r7b-12-2024) and RAG
Extract bibliographical metadata from PDFs
Identify named entities in text
Ask questions about air quality data with pre-built prompts or your own queries
Semantic Deduplication is a powerful tool designed to identify and remove duplicate texts from datasets. It goes beyond simple exact text matching by using advanced natural language processing (NLP) to detect semantically similar content. This means it can recognize texts that convey the same meaning even if they are written differently.
What datasets does Semantic Deduplication support?
Semantic Deduplication is optimized for HuggingFace datasets but can work with other text-based datasets after proper formatting.
How accurate is Semantic Deduplication?
Accuracy depends on the complexity of the texts. Advanced NLP models ensure high accuracy, but human review is recommended for critical datasets.
Can I use Semantic Deduplication for non-English texts?
Yes! Semantic Deduplication supports multiple languages, making it versatile for global datasets.