1 रिपॉजिटरी
Processes for training encoder-decoder architectures to map input sequences to target sequences.
Distinct from Sequence-to-Sequence Models: Distinct from Sequence-to-Sequence Models: focuses on the training process and execution logic rather than the neural network architecture.
Explore 1 awesome GitHub repository matching artificial intelligence & ml · Training Workflows. Refine with filters or upvote what's useful.
SimpleTransformers is a high-level framework for training and fine-tuning transformer models for diverse natural language processing tasks. It functions as a toolkit for developing text classification, named entity recognition, and question answering models, while also serving as a sequence-to-sequence tool and a text embedding generator. The library distinguishes itself by providing a multi-modal model trainer capable of processing and classifying data that combines both text and image inputs. It further supports specialized workflows for conversational AI training, language model generation
Trains encoder-decoder architectures for text transformation tasks such as language translation and summarization.