Search Results for "objects"

Datachain enables multimodal API calls and local AI inferences to run in parallel over many samples as chained operations. The resulting datasets can be saved, versioned, and sent directly to PyTorch and TensorFlow for training. Datachain can persist features of Python objects returned by AI models, and enables vectorized analytical operations over them. The typical use cases are data curation, LLM analytics and validation, image segmentation, pose detection, and GenAI alignment. Datachain is especially helpful if batch operations can be optimized – for instance, when synchronous API calls can be parallelized or where an LLM API offers batch processing.

...A tool for profiling the contents of BER encoded files • JBerd Flattener. A tool for converting BER encoded files to flat files for processing by other facilities • JBerd Decoder objects. A set of Java facilities for writing BER applications that require BER decoding Go to the "files" section (link at the top of this page) to download a pdf of detailed documentation. Andrew Forsyth

...With its simple and powerful schema subsystem it takes charge of very large heterogeneous data sets. The software consist of an API and a generic implementation layer running on top of an SQL or a NoSQL system. Applications can mix objects from multiple ChronoDB databases.