Chug simplifies working with multi-modal data.
GitHub has introduced Chug, a library aimed at streamlining the training process for tasks involving images, documents, and text. This tool is equipped with on-the-fly PDF decoding and functionalities accommodating different data types. Designed with versatility in mind, it builds on popular frameworks like webdataset and Hugging Face datasets to facilitate its integration.
The pliable design of Chug means its components, including various functions and classes, can operate as standalone elements or in conjunction with other data sources. This allows for a smoother and more efficient workflow when navigating the complexities of multi-modal data training.
Read more: Github