| Vision-Language Foundation | |
| ========================== | |
| Humans naturally process information using multiple senses like sight and sound. Similarly, multimodal learning aims to create models that handle different data types, such as images, text, and audio. There's a growing trend in models that combine vision and language, like OpenAI's CLIP. These models excel at tasks like aligning image and text features, image captioning, and visual question-answering. Their ability to generalize without specific training offers many practical uses. Please refer to `NeMo Framework User Guide for Multimodal Models <https://docs.nvidia.com/nemo-framework/user-guide/latest/multimodalmodels/index.html>`_ for detailed support information. | |
| .. toctree:: | |
| :maxdepth: 1 | |
| datasets | |
| configs | |
| checkpoint | |
| clip | |