diff --git a/word_language_model/README.md b/word_language_model/README.md
index 254b726585..54d53cf0f9 100644
--- a/word_language_model/README.md
+++ b/word_language_model/README.md
@@ -1,5 +1,15 @@
# Word-level Language Modeling using RNN and Transformer
+## Requirements
+
+Just running the following command to get started. Actually we just need the torch.
+
+```bash
+pip install -r requirements.txt
+```
+
+## Usage
+
This example trains a multi-layer RNN (Elman, GRU, or LSTM) or Transformer on a language modeling task. By default, the training script uses the Wikitext-2 dataset, provided.
The trained model can then be used by the generate script to generate new text.
@@ -54,3 +64,19 @@ python main.py --cuda --emsize 650 --nhid 650 --dropout 0.5 --epochs 40 --tied
python main.py --cuda --emsize 1500 --nhid 1500 --dropout 0.65 --epochs 40
python main.py --cuda --emsize 1500 --nhid 1500 --dropout 0.65 --epochs 40 --tied
```
+
+To generate samples from the default model checkpoint, just use the the `generate.py` script, which accepts the following arguments:
+
+```bash
+optional arguments:
+ -h, --help show this help message and exit
+ --data DATA location of the data corpus
+ --checkpoint MODEL model checkpoint to use
+ --outf OUTPUT output file for generated text
+ --words WORDS number of words to generate
+ --seed SEED random seed
+ --cuda use CUDA
+ --mps enable GPU on macOS
+ --temperature TEMP temperature - higher will increase diversity
+ --log-interval N report interval
+```
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