Update README.md

README.md

@@ -11,7 +11,7 @@ license: apache-2.0
 
 # 📚 Institutional Books Topic Classifier
 
-This model was trained as part of the analysis and experiments performed in preparation of the release of the [Institutional Books 1.0 dataset](https://huggingface.co/collections/instdin/institutional-books-68366258bfb38364238477cf).
+This model was trained as part of the analysis and refinements performed in preparation of the release of the [Institutional Books 1.0 dataset](https://huggingface.co/collections/instdin/institutional-books-68366258bfb38364238477cf).
 
 We used this text classifier to assign 1 of 20 topics, derived from the first level of the [Library of Congress' Classification Outline](https://www.loc.gov/catdir/cpso/lcco/), to individual volumes.
 
@@ -23,11 +23,11 @@ Complete experimental setup and results are available in our [technical report](
 ## Input format 
 Book metadata, formated as follows:
 ```
-Title: Full title of the book 
-Author: Lorem Ipsum   
-Year: 1852
+Title: A treatise on analytical geometry of tree dimensions, containing the theory of curve surfaces and of curves of double curvature. 
+Author: Hymers, J.   
+Year: 1848
 Language: English
-General Note: A great book
+General Note: Example of a general note
 ```
 
 All of the fields listed in this example are optional.
@@ -76,6 +76,24 @@ All of the fields listed in this example are optional.
 
 Post-training benchmark accuracy: 97.8% (978/1000) 
 
+## Quickstart
+
+```python
+from transformers import pipeline
+
+to_label = """
+Title: A treatise on analytical geometry of tree dimensions, containing the theory of curve surfaces and of curves of double curvature. 
+Author: Hymers, J.   
+Year: 1848
+Language: English
+General Note: Example of a general note
+"""
+
+pipe = pipeline("text-classification", model="instdin/institutional-books-topic-classifier-bert")
+result = pile(to_label.strip())
+print(result[0]) # {'label': 'SCIENCE', 'score': 0.9996894598007202}
+```
+
 ## Cite
 ```
 TBD