Datasaur Dinamic
Datasaur Dinamic enables data labeling to train a model natively. It creates a ready-to-use model directly from Datasaur.
Last updated
Datasaur Dinamic enables data labeling to train a model natively. It creates a ready-to-use model directly from Datasaur.
Last updated
Datasaur Dinamic is an ideal solution for users who prefer to obtain a trained model directly rather than labeled data. It is integrated with Amazon SageMaker and Hugging Face AutoTrain. It supports row-based tasks with Amazon SageMaker and Hugging Face AutoTrain, and token-based tasks exclusively with Hugging Face AutoTrain.
Using Datasaur Dinamic offers several benefits:
Automated Model Training: Streamline the process of training machine learning models using labeled data.
Efficient Labeling: Use the trained models for ML-assisted labeling, improving the efficiency and accuracy of future labeling tasks.
Integration with Applications: Deploy the trained models directly into applications, enhancing functionality with precise data insights.
Please ensure that you have a minimum of 10 rows or sentences of labeled data for effective utilization of Datasaur Dinamic.
Service Providers | Supported Project Type | Configurations |
---|---|---|
Row Based | ||
Row Based and Span Based |