Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you if: you're new to few-shot learning and want to learn; or you're looking for reliable, clear and easily usable code that you can use for your projects. ...
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification. - easy-few-shot-learning/setup.py at master · sicara/easy-few-shot-learning
多模态模型(Multimodal Models)、知识增强模型(Knowledge-enhanced Models)等开源和自研模型,包含自行实现的数据仓库(DataHub),提供了包括Adam、AdamW、SGD等丰富的优化器,涵盖监督学习(Supervised Learning)、小样本学习(Few-shot Learning)以及迁移学习(Transfer Learning)等在内的场景。
Few-shot learning aims at leveraging knowledge learned by one or more deep learning models, in order to obtain good classification performance on new problems, where only a few labeled samples per class are available. Recent years have seen a fair number of works in the field, introducing metho...
训练语言模型(Pre-trained Language Model)、多模态模型(Multimodal Models)、知识增强模型(Knowledge-enhanced Models)等开源和自研模型,包含自行实现的数据仓库(DataHub),提供了包括Adam、AdamW、SGD等丰富的优化器,涵盖监督学习(Supervised Learning)、小样本学习(Few-shot Learning)以及迁移学习(Transfer Learning)等在...
[1]https://github.com/alibaba/EasyNLP[2]https://github.com/alibaba/EasyNLP/tree/master/examples/knowledge_distillation[3]https://github.com/alibaba/EasyNLP/tree/master/examples/fewshot_learning[4]https://github.com/alibaba/EasyNLP/tree/master/examples/landing_large_ptms[5]达摩院NLP团队：https...
登陆大型PTM。 EasyNLP 提供了基于提示的few-shot 学习能力,允许用户只用少量训练样本微调PTMs 以获得良好的效果。同时,提供知识蒸馏功能,帮助快速将大型模型提炼成小型高效模型,方便在线部署。 与开源社区兼容。 EasyNLP 拥有丰富的 API,支持使用 PAI 的分布式学习框架训练来自其他开源库(例如 Huggingface/Transformers2...
[3]https://github.com/alibaba/EasyNLP/tree/master/examples/fewshot_learning [4]https://github.com/alibaba/EasyNLP/tree/master/examples/landing_large_ptms [5]达摩院NLP团队:https://github.com/alibaba/AliceMind [6]文本风控解决方案:https://help.aliyun.com/document_detail/311210.html ...
[3]https://github.com/alibaba/EasyNLP/tree/master/examples/fewshot_learning [4]https://github.com/alibaba/EasyNLP/tree/master/examples/landing_large_ptms [5]达摩院NLP团队:https://github.com/alibaba/AliceMind [6]文本风控解决方案:https://help.aliyun.com/document_detail/311210.html ...
小样本学习 (Few-Shot Learning) 算法简介 PET基于Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference论文策略实现, 基于人工知识设计 Prompt, 将下游目标任务转换为完形填空任务来充分挖掘预训练模型中的知识, 显著提升模型效果。