Bag-of-Word Model Application Similar Image SearchPre-trainingDNN De-noising auto-encoder contractive... picture. Focusing on CODE similarity induce better result.Pre-trainingDNN Use Auto-encoder to do 阅读笔记-GROVER: Self-supervised Message PassingTransformer on Large-scale Molecular Data ...
The foundation of our model is BERT, a cutting-edge pre-trained language model introduced by Devlin et al.19. BERT’s architecture is based on the Transformer model28, which employs self-attention mechanisms to process input sequences in parallel, capturing intricate contextual relationships between...
GPT (Generative Pre-trained Transformer): This language model learns by predicting the next word in a sequence, helping the model learn grammar and semantic structures. Computer Vision: Image Inpainting: This technique involves hiding a part of an image and training the model to predict the missin...
Specifically, Google recently introduced Bidirectional Encoded Representations of Transformers (BERT), a transformer architecture that serves as an English language model trained on a corpus of over 800 million words in the general domain13. BERT encodes bidirectional representations of text using self-...
你可以直接在模型页面上测试大多数model hub上的模型。 我们也提供了私有模型托管、模型版本管理以及推理API。 这里是一些例子: 用BERT 做掩码填词 用Electra 做命名实体识别 用GPT-2 做文本生成 用RoBERTa 做自然语言推理 用BART 做文本摘要 用DistilBERT 做问答 ...
The last few years have seen the rise oftransformerdeep learning architectures to build natural language processing (NLP) model families. The adaptations of the transformer architecture in models such as BERT, RoBERTa, T5, GPT-2, and DistilBERT outperform previous NLP models on a wide...
With just a few lines of code, you can instantly debug, compare, and reproduce your models—architecture, hyperparameters, git commits, model weights, GPU usage, datasets, and predictions—while collaborating with your teammates. W&B Sweeps...
The popularization of the transformer architecture [1] in the past few years has led to rapid advances in natural language processing (NLP). Many benchmarks are now dominated by pre-trained language models (PLMs) that learn to model language using unlabeled corpora. There are many PLM architec...
In 2018, Google proposed the bidirectional encoder representations from transformers (BERT) model [20], which is a deep neural network model based on the transformer architecture. The main contribution of BERT is the introduction of pre-training. BERT is pre-trained on a large-scale unlabeled cor...
图 1 本文所提模型总体结构图 Fig.1 Overallstructurediagramofmodelproposedinthispaper 3.1 语句编码器 本文模型将原文档 转化为词向量序列,然后将其输入双 向长短时记忆网络(BiLSTM)中进行编码. 在 BiLSTM 结构中 ,前向网络正向读取输入序列以计算前向隐藏状态向量 ,后向网络反向读取输入序列以计算反向隐藏状态...