Design neural network models and generate multimodal datasets
Clean and process datasets
Generate dataset for machine learning
Display instructional dataset
Data annotation for Sparky
Create a large, deduplicated dataset for LLM pre-training
Explore datasets on a Nomic Atlas map
Organize and process datasets for AI models
Explore and manage datasets for machine learning
Upload files to a Hugging Face repository
Label data efficiently with ease
Create and manage AI datasets for training models
Multimodal Network Designer is a powerful tool for designing neural network models and generating multimodal datasets. It is specifically tailored for AI and machine learning tasks that involve multiple data types, such as images, text, audio, and more. This tool simplifies the process of creating and managing complex datasets and models, making it easier to work on cutting-edge AI projects.
What types of data does Multimodal Network Designer support?
Multimodal Network Designer supports a wide range of data types, including images, text, audio, and video, making it ideal for diverse AI applications.
How can I handle imbalanced datasets in Multimodal Network Designer?
The tool offers advanced data augmentation and sampling techniques to address imbalanced datasets and ensure robust model training.
Can I export models created in Multimodal Network Designer?
Yes, models can be exported in multiple formats, including TensorFlow, PyTorch, and ONNX, for deployment in various environments.