Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: bert

영문 디렉토리

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

7.7K
Stars
77/100
신뢰
카테고리: ml-automation감사

Bringing BERT into modernity via both architecture changes and scaling

1.7K
Stars
76/100
신뢰
카테고리: rag-knowledge감사

text2vec, text to vector. 文本向量表征工具,把文本转化为向量矩阵,实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型,开箱即用。

5.0K
Stars
79/100
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카테고리: rag-knowledge감사

Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)

3.1K
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79/100
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카테고리: ml-automation감사

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码,实战教程。

6.4K
Stars
70/100
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카테고리: ml-automation감사

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

2.4K
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74/100
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카테고리: ml-automation감사

BERT score for text generation

1.9K
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69/100
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카테고리: ml-automation감사

中文长文本分类、短句子分类、多标签分类、两句子相似度(Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN

1.8K
Stars
72/100
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카테고리: rag-knowledge감사

自然语言处理(nlp),小姜机器人(闲聊检索式chatbot),BERT句向量-相似度(Sentence Similarity),XLNET句向量-相似度(text xlnet embedding),文本分类(Text classification), 实体提取(ner,bert+bilstm+crf),数据增强(text augment, data enhance),同义句同义词生成,句子主干提取(mainpart),中文汉语短文本相似度,文本特征工程,keras-http-service调用

1.5K
Stars
70/100
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카테고리: support-automation감사

基于知识图谱的问答系统,BERT做命名实体识别和句子相似度,分为online和outline模式

1.5K
Stars
70/100
신뢰
카테고리: rag-knowledge감사

A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).

1.3K
Stars
73/100
신뢰
카테고리: rag-knowledge감사