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Tensorflow implementation of "Language Modeling with Gated Convolutional Networks"
| Date | Stars |
|---|---|
| 2026-07-31 | 274 |
| 2026-08-03 | 274 |
| 2026-09-20 | 274 |
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# Language Modeling with Gated Convolutional Networks This is a Tensorflow implementation of Facebook AI Research Lab's paper: [Language Modeling with Gated Convolutional Networks](https://arxiv.org/abs/1612.08083). This paper applies a convolutional approach to language modelling with a novel Gated-CNN model. ## Architecture  ## Requirements - Download and extract the [Google 1 Billion Word dataset](http://www.statmt.org/lm-benchmark/1-billion-word-language-modeling-benchmark-r13output.tar.gz) in the `data` folder. - [TensorFlow 0.12.1](https://www.tensorflow.org/) ## Usage To train the model using the default hyperparameters: ``` $ python main.py $ tensorboard --logdir=logs --host=0.0.0.0 ``` Check `main.py` for tunable hyperparameter flags. ## TODO - [ ] Replace NCE loss with Adaptive Softmax. - [ ] Remove restricted training on fixed sized sentences (20, for now) and extend to account for all varied sentence lenghts. - [ ] Implement Weight Normalisation for faster convergence. - [ ] Train extensively on deeper models to match the results with the paper.
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matched fp:97032bd1898ad5ab, llm:Repository description: 'Tensorflow implementation of "Language Modeling with Gated Convolutional Networks"' (Python).
matched fp:97032bd1898ad5ab, llm:Repository description: 'Tensorflow implementation of "Language Modeling with Gated Convolutional Networks"' (Python).