Update README.md

README.md

@@ -15,22 +15,28 @@ pip install lens-metric
 ```
 
 ```python
-from lens import download_model
-from lens.lens_salsa import LENS_SALSA
-
-model_path = download_model("davidheineman/lens-salsa")
-lens_salsa = LENS_SALSA(model_path)
-
-score = lens_salsa.score(
-    complex = [
-        "They are culturally akin to the coastal peoples of Papua New Guinea."
-    ],
-    simple = [
-        "They are culturally similar to the people of Papua New Guinea."
-    ]
-)
+from lens import download_model, LENS_SALSA
+
+lens_salsa_path = download_model("davidheineman/lens-salsa")
+lens_salsa = LENS_SALSA(lens_salsa_path)
+
+complex = [
+    "They are culturally akin to the coastal peoples of Papua New Guinea."
+]
+simple = [
+    "They are culturally similar to the people of Papua New Guinea."
+]
+
+scores, word_level_scores = lens_salsa.score(complex, simple, batch_size=8, devices=[0])
+print(scores) # [72.40909337997437]
+
+# LENS-SALSA also returns an error-identification tagging, recover_output() will return the tagged output
+tagged_output = lens_salsa.recover_output(word_level_scores, threshold=0.5)
+print(tagged_output)
 ```
 
+For an example, please see the [quick demo Google Collab notebook](https://colab.research.google.com/drive/1rIYrbl5xzL5b5sGUQ6zFBfwlkyIDg12O?usp=sharing).
+
 ## Intended uses
 
 Our model is intented to be used for **reference-free simplification evaluation**. Given a source text and its translation, outputs a single score between 0 and 1 where 1 represents a perfect simplification and 0 a random simplification. LENS-SALSA was trained on edit annotations of the SimpEval dataset, which covers manually-written, complex Wikipedia simplifications. We have not evaluated our model on non-English languages or non-Wikipedia domains.