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backpropBackprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
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Mutual labels: transformers, language-model
wechselCode for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
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Mutual labels: transformers, language-model
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KoELECTRA-PipelineTransformers Pipeline with KoELECTRA
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COCO-LM[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
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miniconsUtility for analyzing Transformer based representations of language.
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Tokenizers💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
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Haystack🔍 Haystack is an open source NLP framework that leverages Transformer models. It enables developers to implement production-ready neural search, question answering, semantic document search and summarization for a wide range of applications.
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Spark NlpState of the Art Natural Language Processing
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PLBARTOfficial code of our work, Unified Pre-training for Program Understanding and Generation [NAACL 2021].
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Nlp ArchitectA model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
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Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
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Nn🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
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gplPowerful unsupervised domain adaptation method for dense retrieval. Requires only unlabeled corpus and yields massive improvement: "GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval" https://arxiv.org/abs/2112.07577
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Mutual labels: transformers
