| karpathy/char-rnn |
11,227 |
|
0 |
0 |
over 2 years ago |
0 |
|
112 |
|
Lua |
| Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch |
| miyosuda/async_deep_reinforce |
560 |
|
0 |
0 |
almost 8 years ago |
0 |
|
34 |
apache-2.0 |
Python |
| Asynchronous Methods for Deep Reinforcement Learning |
| wojciechz/learning_to_execute |
457 |
|
0 |
0 |
about 10 years ago |
0 |
|
2 |
apache-2.0 |
Lua |
| Learning to Execute |
| thushv89/attention_keras |
429 |
|
0 |
0 |
about 3 years ago |
0 |
|
11 |
mit |
Python |
| Keras Layer implementation of Attention for Sequential models |
| sjsdfg/dl4j-tutorials |
429 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
mit |
Java |
| dl4j 基础教程 配套视频：https://space.bilibili.com/327018681/#/ |
| lelechen63/ATVGnet |
239 |
|
0 |
0 |
about 3 years ago |
0 |
|
25 |
|
Python |
| CVPR 2019 |
| zhangzibin/char-rnn-chinese |
190 |
|
0 |
0 |
over 9 years ago |
0 |
|
2 |
|
Lua |
| Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch. Based on code of https://github.com/karpathy/char-rnn. Support Chinese and other things. |
| zhongkaifu/Seq2SeqSharp |
188 |
|
0 |
3 |
over 2 years ago |
1 |
May 09, 2022 |
6 |
other |
C# |
| Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, x86, x64, ARM), multimodal model for text and images and so on. |
| okuchaiev/f-lm |
156 |
|
0 |
0 |
almost 7 years ago |
0 |
|
1 |
mit |
Python |
| Language Modeling |
| riejohnson/ConText |
116 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
gpl-3.0 |
C++ |
| ConText v4: Neural networks for text categorization |
