Emse_best Answer Prediction
Dataset, scripts, and additional material for the EMSE submission "Best-Answer Prediction in Technical Q&A Sites"
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Biobert | 1,602 | a year ago | 49 | other | Python | |||||
| Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining | ||||||||||
| Pretrain Gnns | 805 | 9 months ago | 29 | mit | Python | |||||
| Strategies for Pre-training Graph Neural Networks | ||||||||||
| Empatheticdialogues | 227 | 3 years ago | 2 | other | Python | |||||
| Dialogue model that produces empathetic responses when trained on the EmpatheticDialogues dataset. | ||||||||||
| Dynamic Training Bench | 214 | 2 years ago | 42 | February 28, 2018 | 1 | mpl-2.0 | Python | |||
| Simplify the training and tuning of Tensorflow models | ||||||||||
| Bert Attributeextraction | 185 | 5 years ago | 2 | Python | ||||||
| USING BERT FOR Attribute Extraction in KnowledgeGraph. fine-tuning and feature extraction. 使用基于bert的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取。 | ||||||||||
| Cosine | 155 | 2 years ago | 3 | mit | Python | |||||
| This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach' (In Proc. of NAACL-HLT 2021). | ||||||||||
| Fractaldb Pretrained Resnet Pytorch | 140 | 2 years ago | 3 | mit | Python | |||||
| Pre-training without Natural Images (ACCV 2020 Best Paper Honorable Mention Award) | ||||||||||
| Finetune Detr | 90 | a year ago | mit | Jupyter Notebook | ||||||
| Fine-tune Facebook's DETR (DEtection TRansformer) on Colaboratory. | ||||||||||
| Fine Tuning | 58 | 3 years ago | 8 | gpl-3.0 | Python | |||||
| Close-Domain fine-tuning for table detection | ||||||||||
| Asset | 42 | 2 years ago | other | Roff | ||||||
| A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations | ||||||||||
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