Explore and annotate datasets for machine learning
Browse TheBloke models' history
ReWrite datasets with a text instruction
Evaluate evaluators in Grounded Question Answering
Display translation benchmark results from NTREX dataset
Explore datasets on a Nomic Atlas map
Validate JSONL format for fine-tuning
Organize and process datasets efficiently
Curate and manage datasets for AI and machine learning
Speech Corpus Creation Tool
Browse and search datasets
Upload files to a Hugging Face repository
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.