Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Tensorflow implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)
| Date | Stars |
|---|---|
| 2026-07-24 | 282 |
| 2026-07-25 | 282 |
| 2026-07-28 | 282 |
| 2026-07-30 | 282 |
| 2026-07-31 | 281 |
| 2026-08-06 | 281 |
Today
— stars today
This week
-1 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# RNN-for-Joint-NLU ## 模型介绍  使用tensorflow r1.3 api，Encoder使用`tf.nn.bidirectional_dynamic_rnn`实现，Decoder使用`tf.contrib.seq2seq.CustomHelper`和`tf.contrib.seq2seq.dynamic_decode`实现。 [原作者Bing Liu的Tensorflow实现](https://github.com/HadoopIt/rnn-nlu) 我的实现相对比较简单，用于学习目的。 ## 使用 ``` python main.py ``` 输出： ``` [Epoch 27] Average train loss: 0.0 Input Sentence : ['what', 'are', 'the', 'flights', 'and', 'prices', 'from', 'la', 'to', 'charlotte', 'for', 'monday', 'morning'] Slot Truth : ['O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-fromloc.city_name', 'O', 'B-toloc.city_name', 'O', 'B-depart_date.day_name', 'B-depart_time.period_of_day'] Slot Prediction : ['O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-fromloc.city_name', 'O', 'B-toloc.city_name', 'O', 'B-depart_date.day_name', 'B-depart_time.period_of_day'] Intent Truth : atis_flight Intent Prediction : atis_flight#atis_airfare Intent accuracy for epoch 27: 0.969758064516129 Slot accuracy for epoch 27: 0.9782146713160718 Slot F1 score for epoch 27: 0.977950943062074 [Epoch 28] Average train loss: 0.0 Input Sentence : ['show', 'me', 'the', 'last', 'flight', 'from', 'love', 'field'] Slot Truth : ['O', 'O', 'O', 'B-flight_mod', 'O', 'O', 'B-fromloc.airport_name', 'I-fromloc.airport_name'] Slot Prediction : ['O', 'O', 'O', 'B-flight_mod', 'O', 'O', 'B-fromloc.airport_name', 'I-fromloc.airport_name'] Intent Truth : atis_flight Intent Prediction : atis_flight Intent accuracy for epoch 28: 0.9717741935483871 Slot accuracy for epoch 28: 0.9794670271393975 Slot F1 score for epoch 28: 0.9792847025495751 ``` ## 细节 博客文章： - [Tensorflow动态seq2seq使用总结（r1.3）](https://github.com/applenob/RNN-for-Joint-NLU/blob/master/tensorflow_dynamic_seq2seq.md)
Excerpt of 1,844 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:356370a0f16c1ca5, topic:tensorflow