The following integrations are developed and maintained by third parties.
H2O Hydrogen Torch#
H2O Hydrogen Torch is a no-code deep learning tool. You can use Neptune to compare and visualize your H2O Hydrogen Torch experiments.
- See the H2O Hydrogen Torch documentation .
H2O LLM Studio#
H2O LLM Studio is a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). It integrates with Neptune to track and visualize all aspects of your experiment in real time.
Modelbit lets you deploy ML models from Jupyter notebooks to production environments with REST APIs. It integrates with Neptune using your Neptune API token so you can log training metadata and model performance to your Neptune projects.
- See Using Neptune with training jobs in the Modelbit documentation.
Open Metric Learning#
OML is a PyTorch-based framework to train and validate the models producing high-quality embeddings. You can enable Neptune logging in OML Pipelines.
RecList is an open source library providing behavioral, "black-box" testing for recommender systems. It supports streaming the results of your tests directly to Neptune, both as metrics and charts.
- See Using third-party tracking tools in the RecList documentation.
- View a video showing this integration in action .
Slideflow is a deep learning library for digital pathology that provides a unified API for building, training, and testing models using Tensorflow or PyTorch. You can enable Neptune logging when working with Slideflow.
Ultralytics YOLO is a cutting-edge, state-of-the-art (SOTA) computer vision model. Ultralytics supports Neptune logging when working with YOLO models.