SimCSE
inltk
| SimCSE | inltk | |
|---|---|---|
| 2 | 1 | |
| 3,255 | 811 | |
| 1.5% | - | |
| 0.0 | 0.0 | |
| 8 months ago | 4 months ago | |
| Python | Python | |
| MIT License | MIT License |
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SimCSE
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BERT-Based Clustering on a Corpus of Genre Samples Kinda Sucks. Why?
Base BERT sentence embeddings are just not good for a couple of reasons and there's some research papers that show this. You can try SimCSE, Google's USE or SBERT as mentioned previously and you'll get better output. It's just an inherent flaw to base BERT that it can't produce good sentence embeddings. Papers have shown you probably will get better scores using GloVe embeddings from scratch than base BERT.
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State of the Art in Sentence Embeddings
To answer your question about sentence embedding SOTA, it is not s-Bert and hasn't been for a while. SimCSE officially takes the crown since it's been presented at a conference, though according to paperswithcode's benchmark leaderboard there are other papers on arxiv that report higher performance on STS and similar tasks such as DCPCSE. Having tried both of these for my use case I found SimCSE to be better but YMMV.
inltk
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Which are top APIs for Indian languages mainly VR, OCR, Speech - Text - Speech?
The best tool will vary a little bit from language to language, but your best bets are probably the Indic NLP Library and iNLTK
What are some alternatives?
PromCSE - Code for "Improved Universal Sentence Embeddings with Prompt-based Contrastive Learning and Energy-based Learning (EMNLP 2022)"
allennlp - An open-source NLP research library, built on PyTorch.
AnnA_Anki_neuronal_Appendix - Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity
DiffCSE - Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"
smaller-labse - Applying "Load What You Need: Smaller Versions of Multilingual BERT" to LaBSE
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
KitanaQA - KitanaQA: Adversarial training and data augmentation for neural question-answering models
ModelNet40-C - Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)