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Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering specialized architectures for both text and vision processing. The framework includes tools for managing the entire model lifecycle, from data preprocessing and tokenization to distributed training and inference. The library features extensive support for model optimization and
PyTorch original implementation of Cross-lingual Language Model Pretraining.
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly train on a text using a pretrained model.
Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the CASL project: http://casl-project.ai/
The main features of asyml/texar are: Natural Language Processing, Pre-trained Language Models, Text Generation, Neural Natural Language Generation.
Projects with overlapping indexed features include: huggingface/transformers — Transformers is a comprehensive library for machine learning that provides a unified interface for training,… codertimo/bert-pytorch. nlpscott/bert-chinese-classification-task — bert中文分类实践. facebookresearch/xlm — PyTorch original implementation of Cross-lingual Language Model Pretraining. minimaxir/textgenrnn — Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines… openbmb/bmlist — A List of Big Models.
