NCRFpp VS zshot

Compare NCRFpp vs zshot and see what are their differences.

NCRFpp

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components. (by jiesutd)
Pytorch Ner sequence-labeling Crf lstm-crf char-rnn char-cnn named-entity-recognition part-of-speech-tagger chunking neural-networks nbest Lstm Cnn Natural Language Processing Artificial intelligence
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zshot

Zero and Few shot named entity & relationships recognition (by IBM)
few-shot few-shot-learning ned Ner relation-extraction zero-shot zero-shot-learning spacy NLP AI Deep Learning Machine Learning named-entity-recognition Natural Language Processing natural-language-understanding nlp-library Pytorch relationship-extraction Transformer
Source Code
ibm.github.io
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NCRFpp zshot
1 2
1,877 316
- 4.1%
0.0 6.6
almost 2 years ago 2 months ago
Python Python
Apache License 2.0 MIT License
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NCRFpp

Posts with mentions or reviews of NCRFpp. We have used some of these posts to build our list of alternatives and similar projects.
  • Speech and Language Processing (3rd ed. draft)
    1 project | news.ycombinator.com | 17 Oct 2021
    They still talk about Hidden Markov Models (HMMs) in quite a bit of detail in the sequence labelling chapter, but you are quite right, Conditional Random Fields (CRFs) and especially neural network based CRFs are in the top rankings when it comes to named entity recognition (NER) and part-of-speech tagging (POS), e.g. see https://github.com/jiesutd/NCRFpp.

zshot

Posts with mentions or reviews of zshot. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing NCRFpp and zshot you can also consider the following projects:

seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).

SimpNet-Deep-Learning-in-a-Shader - A trainable convolutional neural network inside a fragment shader

bllip-parser - BLLIP reranking parser (also known as Charniak-Johnson parser, Charniak parser, Brown reranking parser) See http://pypi.python.org/pypi/bllipparser/ for Python module.

thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

GoLLIE - Guideline following Large Language Model for Information Extraction

nn-morse - Decode morse using a neural network

DeepKE - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction

pytorch-partial-crf - CRF, Partial CRF and Marginal CRF in PyTorch

ARElight - Granular Viewer of Sentiments Between Entities in Massively Large Documents and Collections of Texts, powered by AREkit

NCRFpp vs seqeval zshot vs transferlearning NCRFpp vs Stanza zshot vs FSL-Mate NCRFpp vs SimpNet-Deep-Learning-in-a-Shader zshot vs bllip-parser NCRFpp vs thinc zshot vs GoLLIE NCRFpp vs nn-morse zshot vs DeepKE NCRFpp vs pytorch-partial-crf zshot vs ARElight