Displaying 1 to 5 from 5 results

NCRFpp - NCRF++, an Open-source Neural Sequence Labeling Toolkit

  •    Python

Sequence labeling models are quite popular in many NLP tasks, such as Named Entity Recognition (NER), part-of-speech (POS) tagging and word segmentation. State-of-the-art sequence labeling models mostly utilize the CRF structure with input word features. LSTM (or bidirectional LSTM) is a popular deep learning based feature extractor in sequence labeling task. And CNN can also be used due to faster computation. Besides, features within word are also useful to represent word, which can be captured by character LSTM or character CNN structure or human-defined neural features. NCRF++ is a PyTorch based framework with flexiable choices of input features and output structures. The design of neural sequence labeling models with NCRF++ is fully configurable through a configuration file, which does not require any code work. NCRF++ is a neural version of CRF++, which is a famous statistical CRF framework.

advanced-tensorflow - Little More Advanced TensorFlow Implementations

  •    Jupyter

Collection of (Little More + Refactored) Advanced TensorFlow Implementations. Try my best to implement algorithms with a single Jupyter Notebook.

Charmanteau-CamReady - Code for "CharManteau: Character Embedding Models For Portmanteau Creation

  •    Python

Abstract: Portmanteaus are a word formation phenomenon where two words are combined to form a new word. We propose character-level neural sequence-to-sequence (S2S) methods for the task of portmanteau generation that are end-to-end-trainable, language independent, and do not explicitly use additional phonetic information. We propose a noisy-channel-style model, which allows for the incorporation of unsupervised word lists, improving performance over a standard source-to-target model. This model is made possible by an exhaustive candidate generation strategy specifically enabled by the features of the portmanteau task. Experiments find our approach superior to a state-of-the-art FST-based baseline with respect to ground truth accuracy and human evaluation. Code/ contains the code. Data/ contains the dataset.

neural-namer - Fantasy name generator in TensorFlow

  •    Python

A character RNN that learns how to emulate the styles of names of different fantasy authors. Recommended process is to setup a Python Virtual environment.




char-rnn-keras - TensorFlow implementation of multi-layer recurrent neural networks for training and sampling from texts

  •    Python

Multi-layer recurrent neural networks for training and sampling from texts, inspired by Andrej Karpathy's article and the original torch source code karpathy/char-rnn. This code is written in Python 3, and it requires the Keras deep learning library.






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