Build a character level language model to generate new dinosaur names
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Updated
Feb 15, 2018 - Python
Build a character level language model to generate new dinosaur names
Text Article generator using using Character level LSTM network.
Lyrics Generation:notes: using LSTM , word2vec Analysis and more
Name generation using RNN. This model was trained for generating indian names. Made using keras.
Notebooks of programming assignments of Sequence Models course of deeplearning.ai on coursera in May-2020
An implementation of "Character-level Convolutional Networks for Text Classification" in Tensorflow. See https://arxiv.org/pdf/1509.01626.pdf.
Official code for Group-Transformer (Scale down Transformer by Grouping Features for a Lightweight Character-level Language Model, COLING-2020).
Sequence Models coding assignments
It aims to write new sentences by learning character units sentences using RNN. As training data, a collection of Shakespeare's novels was used.
Recurrent neural network for building a character-level language model and its application to generating new dinosaur names
A causal intervention framework to learn robust and interpretable character representations inside subword-based language models
In this project, I worked with a small corpus consisting of simple sentences. I tokenized the words using n-grams from the NLTK library and performed word-level and character-level one-hot encoding. Additionally, I utilized the Keras Tokenizer to tokenize the sentences and implemented word embedding using the Embedding layer. For sentiment analysis
This is a diacritization model for Arabic language. This model was built/trained using the Tashkeela: the Arabic diacritization corpus on Kaggle
This repository contains the code and PLODv2 dataset to train character-level language models (CLM) for abbreviation and long-form detection released with our LREC-COLING 2024 publication
retro style tokenization for language models
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