Update README.md

README.md

@@ -7,24 +7,28 @@ widget:
   - text: Rigtig god service!
 ---
 
-Classification model for short customer reviews written in Danish. 
+# What is this?
+
+BERT classification model for short customer reviews written in Danish. 
 
 The model uses 5 classes ranging from 1-5 stars:
 
-* ⭐ (poor)
-* ⭐⭐
-* ⭐⭐⭐
-* ⭐⭐⭐⭐
+* ⭐ (very poor)
+* ⭐⭐ (poor)
+* ⭐⭐⭐ (neutral)
+* ⭐⭐⭐⭐ (good)
 * ⭐⭐⭐⭐⭐ (very good)
 
-The model is fine-tuned using a pretrained [Danish BERT model]("Maltehb/danish-bert-botxo").
+The model is fine-tuned using the pre-trained [Danish BERT model]("Maltehb/danish-bert-botxo").
+
+# How to use
 
 Test the model using the [🤗Transformers](https://github.com/huggingface/transformers) library pipeline:
 
 ```python
 from transformers import pipeline
 
-classifier = pipeline("sentiment-analysis", model="danish-bert-review-sentiment")
+classifier = pipeline("sentiment-analysis", model="KennethTM/danish-bert-review-sentiment")
 classifier("Intet virkede og ingen hjælp at hente.")
 
 #[{'label': '⭐', 'score': 0.4953940808773041}]
@@ -35,6 +39,6 @@ Or load it using the Auto* classes:
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-model = AutoModelForSequenceClassification.from_pretrained("danish-bert-review-sentiment")
-tokenizer = AutoTokenizer.from_pretrained("danish-bert-review-sentiment")
+model = AutoModelForSequenceClassification.from_pretrained("KennethTM/danish-bert-review-sentiment")
+tokenizer = AutoTokenizer.from_pretrained("KennethTM/danish-bert-review-sentiment")
 ```