Update README.md

README.md

@@ -68,21 +68,24 @@ To get started, simply install `datasets` with `pip install datasets` and load t
 from datasets import load_dataset
 from huggingface_hub import snapshot_download
 
+# Load the validation split
 valid = load_dataset("McGill-NLP/weblinx", split="validation")
 
+# Download the input templates and use the LLaMA one
 snapshot_download(
-    "McGill-NLP/WebLINX", repo_type="dataset", allow_patterns="templates/llama.txt", local_dir="./"
+    "McGill-NLP/WebLINX", repo_type="dataset", allow_patterns="templates/", local_dir="./"
 )
 with open('templates/llama.txt') as f:
     template = f.read()
 
+# To get the input text, simply pass a turn from the valid split to the template
 turn = valid[0]
 turn_text = template.format(**turn)
 ```
 
 You can now use `turn_text` as an input to LLaMA-style models. For example, you can use Sheared-LLaMA:
-```python
 
+```python
 from transformers import pipeline
 
 action_model = pipeline(
@@ -112,7 +115,7 @@ For more information on how to use this data using our [official library](https:
 If you use our dataset, please cite our work as follows:
 
 ```bibtex
-@misc{lù2024weblinx,
+@misc{lu-2024-weblinx,
       title={WebLINX: Real-World Website Navigation with Multi-Turn Dialogue}, 
       author={Xing Han Lù and Zdeněk Kasner and Siva Reddy},
       year={2024},