Huggingface

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Huggingface is an API providing pre-trained transformers models implemented in PyTorch and Tensorflow, which are extremely useful for a variety of NLP tasks.

Its Transformers library (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG).

Features:

– High performance on NLU and NLG tasks

– Low barrier to entry for educators and practitioners

– State-of-the-art NLP for everyone

  • Deep learning researchers
  • Hands-on practitioners
  • AI/ML/NLP teachers and educators

– Lower compute costs, smaller carbon footprint

  • Researchers can share trained models instead of always retraining
  • Practitioners can reduce compute time and production costs
  • Dozens of architectures with over 1,000 pretrained models, some in more than 100 languages

– Choose the right framework for every part of a model’s lifetime

  • Train state-of-the-art models in 3 lines of code
  • Deep interoperability between TensorFlow 2.0 and PyTorch models
  • Move a single model between TF2.0/PyTorch frameworks at will
  • Seamlessly pick the right framework for training, evaluation, production