learning/annotated_deep_learning_paper_implementations
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Varuna Jayasiri
2021-01-14 10:20:21 +05:30
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labml_nn/__init__.py
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@ -21,6 +21,7 @@ contains implementations for
and
[relative multi-headed attention](https://lab-ml.com/labml_nn/transformers/relative_mha.html).
* [GPT Architecture](https://lab-ml.com/labml_nn/transformers/gpt)
* [kNN-LM: Generalization through Memorization](https://lab-ml.com/labml_nn/transformers/knn)
* [Feedback Transformer](https://lab-ml.com/labml_nn/transformers/feedback)

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labml_nn/transformers/__init__.py
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@ -18,6 +18,10 @@ and derivatives and enhancements of it.
* [Transformer Encoder and Decoder Models](models.html)
* [Fixed positional encoding](positional_encoding.html)
## [GPT Architecture](gpt)
This is an implementation of GPT-2 architecture.
## [kNN-LM](knn)
This is an implementation of the paper

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readme.md
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@ -27,6 +27,7 @@ contains implementations for
and
[relative multi-headed attention](https://lab-ml.com/labml_nn/transformers/relative_mha.html).
* [GPT Architecture](https://lab-ml.com/labml_nn/transformers/gpt)
* [kNN-LM: Generalization through Memorization](https://lab-ml.com/labml_nn/transformers/knn)
* [Feedback Transformer](https://lab-ml.com/labml_nn/transformers/feedback)