NCRFpp
thinc
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| NCRFpp | thinc | |
|---|---|---|
| 1 | 4 | |
| 1,877 | 2,787 | |
| - | 0.5% | |
| 0.0 | 6.9 | |
| almost 2 years ago | 5 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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NCRFpp
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Speech and Language Processing (3rd ed. draft)
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.
thinc
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JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation
Agree, though I wouldn’t call PyTorch a drop-in for NumPy either. CuPy is the drop-in. Excepting some corner cases, you can use the same code for both. Thinc’s ops work with both NumPy and CuPy:
https://github.com/explosion/thinc/blob/master/thinc/backend...
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Tinygrad: A simple and powerful neural network framework
I love those tiny DNN frameworks, some examples that I studied in the past (I still use PyTorch for work related projects) :
thinc.by the creators of spaCy https://github.com/explosion/thinc
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good examples of functional-like python code that one can study?
thinc - defining neural nets in functional way jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable
- thinc - A refreshing functional take on deep learning, compatible with your favorite libraries
What are some alternatives?
zshot - Zero and Few shot named entity & relationships recognition
quantulum3 - Library for unit extraction - fork of quantulum for python3
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
SimpNet-Deep-Learning-in-a-Shader - A trainable convolutional neural network inside a fragment shader
extending-jax - Extending JAX with custom C++ and CUDA code
nn-morse - Decode morse using a neural network
dm-haiku - JAX-based neural network library
pytorch-partial-crf - CRF, Partial CRF and Marginal CRF in PyTorch
AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.