Update README.md

README.md

@@ -9,7 +9,9 @@ pipeline_tag: text-classification
 
 # HamzaFarhan/PDFSegs
 
-This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
+This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification.
+<br>The labels are: 'Work Experience', 'Education', and 'Certifications'.
+<br>The model has been trained using an efficient few-shot learning technique that involves:
 
 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
 2. Training a classification head with features from the fine-tuned Sentence Transformer.
@@ -30,7 +32,7 @@ from setfit import SetFitModel
 # Download from Hub and run inference
 model = SetFitModel.from_pretrained("HamzaFarhan/PDFSegs")
 # Run inference
-preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
+preds = model(['I worked at Google for 5 years.','I have a PhD in Computer Science.'])
 ```
 
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