Tool for pretrained models JGLUE - JGLUE: Japanese General Language Understanding Evaluation ginza-transformers - Use custom tokenizers in spacy-transformers t5_japanese_dialogue_generation - T5による会話生成 japanese_text_classification - To investigate various DNN text classifiers including MLP, CNN, ...
Starcoder 2, family of code generation models GPT Fast, fast and hackable pytorch native transformer inference Mixtral Offloading, run Mixtral-8x7B models in Colab or consumer desktops Llama Llama Recipes TinyLlama Mosaic Pretrained Transformers (MPT) ...
Built-in algorithms and pretrained models in Amazon SageMaker Built-in algorithms train machine learning models, pre-trained models solve common problems, supervised learning classifies and predicts numeric values, unsupervised learning clusters and detects anomalies, textual analysis classifies, summarizes, ...
Built-in algorithms and pretrained models in Amazon SageMaker Built-in algorithms train machine learning models, pre-trained models solve common problems, supervised learning classifies and predicts numeric values, unsupervised learning clusters and detects anomalies, textual analysis classifies, summarizes, ...
6150 A COMPARATIVE STUDY ON ANNOTATION QUALITY OF CROWDSOURCING AND LLM VIA LABEL AGGREGATION 7551 A COMPARISON OF PARAMETER-EFFICIENT ASR DOMAIN ADAPTATION METHODS FOR UNIVERSAL SPEECH AND LANGUAGE MODELS 10309 A complete method for the 3D reconstruction of axonal pathways from 2 orthogonal 3D OCT ima...
sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification. MUSE: A library for Multilingual Unsupervised or Supervised word Embeddings nmtpytorch: Neural Machine Translation Framework in PyTorch. pytorch-wavenet: An implementation of WaveNet with fast generation ...
Pretrained language models are trained on huge unlabeled corpora. For example, RoBERTa[6]is trained on over 160GB of text, including encyclopedias, news articles, literary works, and web content. The representations learned by these models achieve excellent performance on tasks containing datasets of...
1. Introduction Deep metric learning (DML) plays a crucial role in a va- riety of applications in computer vision, such as image re- trieval [28, 19], clustering [10], and transfer learning [20]. In addition, DML is a good solution for challenging extreme classification settings [22, ...
6100+ pretrained-models.pytorch: PyTorch 预训练卷积神经网络:NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN 等等。该项目的目标是帮助复制研究论文结果。 1000- pytorch_fft: CUDA FFTs的PyTorch包装器。 1000- caffe_to_torch_to_pytorch: Caffe模型转PyTorch/Torch模型,Torch模型转PyT...
Evaluating Pretrained Transformer-based Models on the Task of Fine-Grained Named Entity Recognition. Cedric Lothritz, Kevin Allix, Lisa Veiber, Tegawendé F. Bissyandé and Jacques Klein Exploring Cross-sentence Contexts for Named Entity Recognition with BERT. Jouni Luoma and Sampo Pyysalo ...