Update README.md

README.md

@@ -12,18 +12,33 @@ model-index:
 # bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract
 
 This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on a labeled dataset provided by CWTS:
-[CWTS Labeled Data].
+[CWTS Labeled Data]
 
-This is NOT the full model being used to tag OpenAlex works with a topic. For that, check out the following github repo:
+This is NOT the full model being used to tag [OpenAlex](https://openalex.org/) works with a topic. For that, check out the following github repo:
 [OpenAlex Topic Classification](https://github.com/ourresearch/openalex-topic-classification)
 
+That repository will also contain information about text preprocessing, modeling, testing, and deployment.
+
 ## Model description
 
-The input data is expected to be in the following format:
+The input data was trained using the following format (so it is recommended the data be in this format as well):
 
 "\<TITLE\> {insert-processed-title-here}\n\<ABSTRACT\> {insert-processed-abstract-here}"
 
-Since this was train
+The quickest way to use this model in Python is with the following code (assuming you have the transformers library installed):
+
+```
+from transformers import pipeline
+
+title = "{insert-processed-title-here}"
+abstract = "{insert-processed-abstract-here}"
+
+classifier = \
+    pipeline(model="OpenAlex/bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract", top_k=10)
+
+classifier(f"""<TITLE> {title}\n<ABSTRACT> {abstract}""")
+
+```
 
 ## Intended uses & limitations