| shibing624/text2vec |
3,610 |
|
0 |
4 |
over 2 years ago |
35 |
September 20, 2023 |
10 |
apache-2.0 |
Python |
| 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。 |
| MaartenGr/KeyBERT |
3,047 |
|
0 |
18 |
about 2 years ago |
16 |
October 05, 2023 |
41 |
mit |
Python |
| Minimal keyword extraction with BERT |
| resemble-ai/Resemblyzer |
2,415 |
|
0 |
1 |
over 2 years ago |
5 |
October 12, 2023 |
34 |
apache-2.0 |
Python |
| A python package to analyze and compare voices with deep learning |
| facebookresearch/SentEval |
1,627 |
|
0 |
0 |
over 4 years ago |
0 |
|
30 |
other |
Python |
| A python tool for evaluating the quality of sentence embeddings. |
| msgi/nlp-journey |
1,563 |
|
0 |
0 |
over 2 years ago |
3 |
April 29, 2020 |
0 |
apache-2.0 |
Python |
| Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0. |
| dhwajraj/deep-siamese-text-similarity |
1,216 |
|
0 |
0 |
almost 6 years ago |
0 |
|
29 |
mit |
Python |
| Tensorflow based implementation of deep siamese LSTM network to capture phrase/sentence similarity using character/word embeddings |
| nlptown/nlp-notebooks |
710 |
|
0 |
0 |
almost 4 years ago |
0 |
|
6 |
|
Jupyter Notebook |
| A collection of notebooks for Natural Language Processing from NLP Town |
| MaartenGr/PolyFuzz |
671 |
|
0 |
2 |
over 2 years ago |
12 |
September 03, 2023 |
22 |
mit |
Python |
| Fuzzy string matching, grouping, and evaluation. |
| kudkudak/word-embeddings-benchmarks |
368 |
|
0 |
0 |
over 5 years ago |
0 |
|
22 |
mit |
Python |
| Package for evaluating word embeddings |
| alexklibisz/elastiknn |
347 |
|
0 |
2 |
about 2 years ago |
29 |
September 27, 2021 |
13 |
apache-2.0 |
Scala |
| Elasticsearch plugin for nearest neighbor search. Store vectors and run similarity search using exact and approximate algorithms. |
