Thomas Wolf
- jxhe/unify-parameter-efficient-tuning
- huggingface/transformers
- microsoft/fastformers
- huggingface/datasets
- huggingface/neuralcoref
- huggingface/naacl_transfer_learning_tutorial
- huggingface/nanotron
- huggingface/pytorch-openai-transformer-lm
- huggingface/evaluate
- huggingface/transfer-learning-conv-ai
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
✨Fast Coreference Resolution in spaCy with Neural Networks
🦄 State-of-the-Art Conversational AI with Transfer Learning
🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI
🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
Repository of code for the tutorial on Transfer Learning in NLP held at NAACL 2019 in Minneapolis, MN, USA
FastFormers - highly efficient transformer models for NLU
An open collection of methodologies to help with successful training of large language models.
Implementation of paper "Towards a Unified View of Parameter-Efficient Transfer Learning" (ICLR 2022)
An open collection of implementation tips, tricks and resources for training large language models