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Add Chinese usage in Tutorial.md #27

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Update Tutorial.md
woailaosang Apr 29, 2019
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zhsang Apr 29, 2019
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fix CPU train --> GPU test, GPU train --> CPU test. But CPU train -->…
zhsang Apr 29, 2019
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remove ujson
woailaosang Apr 29, 2019
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remove glove for model_zoo/demo/conf.json
woailaosang Apr 29, 2019
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modify glove for Tutorial.md
woailaosang Apr 29, 2019
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add nltk.download('punkt') in problem.py
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Merge branch 'dev/zj' of github.com:Microsoft/NeuronBlocks into dev/zj
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woailaosang May 5, 2019
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fix CPU train --> multi GPUs test.
woailaosang May 5, 2019
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Add CPU/GPU table for README.md
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Add CPU/GPU table for README_zh_CN.md
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woailaosang May 6, 2019
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add Chinese support
woailaosang May 6, 2019
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add license for core/Stopwords.py
woailaosang May 6, 2019
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modify conf_chinese_sentiment_analysis_bilstm.json
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add nltk.download('stopwords')
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Update README_zh_CN.md
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woailaosang May 8, 2019
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add language supported check
woailaosang May 8, 2019
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Update Tutorial.md
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modify glove for Tutorial.md

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woailaosang committed Apr 29, 2019
commit 49c587bd928dcd52698e64612bbf71502eea7105
@@ -25,7 +25,7 @@

## <span id="installation">Installation</span>

*Note: NeuronBlocks is based on Python 3.6*
*Note: NeuronBlocks is based on **Python 3.6***

1. Clone this project.
```bash
@@ -37,7 +37,7 @@
pip install -r requirements.txt
```

3. Install PyTorch (*NeuronBlocks supports PyTorch version 0.4.1 currently*).
3. Install PyTorch (*NeuronBlocks supports **PyTorch 0.4.1** currently*).

For **Linux**, run the following command:
```bash
@@ -50,15 +50,11 @@

## <span id="quick-start">Quick Start</span>

Get started by trying the given examples.
Get started by trying the given examples. For **Windows**, we suggest you to use PowerShell instead of CMD.

*Tips: in the following instruction, PROJECTROOT denotes the root directory of this project.*

```bash
# get GloVe pre-trained word vectors
cd PROJECT_ROOT/dataset
bash get_glove.sh
# train
cd PROJECT_ROOT
python train.py --conf_path=model_zoo/demo/conf.json
@@ -207,6 +203,11 @@ A model visualizer is provided for visualization and configuration correctness c

In Model Zoo, we provide a suite of NLP models for common NLP tasks, in the form of JSON configuration files. You can pick one of existing models (JSON config files) in Model Zoo to start model training quickly, or build your own models by modifying the JSON config file to suit your specific task.

*Note: Before trying models in NLP tasks, please download [GloVe](https://nlp.stanford.edu/projects/glove/) firstly via following commands.*
```bash
cd PROJECT_ROOT/dataset
./get_glove.sh
```

### <span id="task-1">Task 1: Text Classification</span>

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