Explore and annotate datasets for machine learning
List of French datasets not referenced on the Hub
Explore and edit JSON datasets
Organize and process datasets using AI
Perform OSINT analysis, fetch URL titles, fine-tune models
Label data for machine learning models
Create a domain-specific dataset project
Speech Corpus Creation Tool
Upload files to a Hugging Face repository
Create a large, deduplicated dataset for LLM pre-training
Organize and invoke AI models with Flow visualization
Explore, annotate, and manage datasets
Organize and process datasets using AI
VisuaLexNER is a powerful tool designed to help users explore and annotate datasets for machine learning. It is particularly tailored for Named Entity Recognition (NER) tasks, making it easier to create and manage high-quality training data. With VisuaLexNER, users can streamline the process of dataset creation, ensuring their data is well-organized and suitable for building accurate machine learning models.
What file formats does VisuaLexNER support for data import?
VisuaLexNER supports CSV, JSON, and plain text files for data import.
How are annotations exported from VisuaLexNER?
Annotations are exported in a structured format (e.g., JSON or CSV) with labeled entities clearly identified.
Can VisuaLexNER be used by teams for collaborative projects?
Yes, VisuaLexNER offers collaboration tools, allowing multiple users to work together on dataset creation and annotation.