Update README.md

README.md

@@ -1,3 +1,14 @@
+---
+license: "mit"
+
+widget:
+- text: "Took the pill, 12 hours later my muscles started to really hurt, then my ribs started to burn so bad I couldn't breath."
+---
+
+This model takes text (narrative of reasctions to medications) as input and returns a predicted severity score for the reaction (LABEL_1 is severe reaction). Please do NOT use for medical diagnosis.
+Example usage:
+
+```python
 import torch
 import tensorflow as tf
 from transformers import RobertaTokenizer, RobertaModel
@@ -5,8 +16,8 @@ from transformers import AutoModelForSequenceClassification
 from transformers import TFAutoModelForSequenceClassification
 from transformers import AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("UVA-MSBA/Mod4_T7")  
-model = AutoModelForSequenceClassification.from_pretrained("UVA-MSBA/Mod4_T7")
+tokenizer = AutoTokenizer.from_pretrained("paragon-analytics/ADRv1")  
+model = AutoModelForSequenceClassification.from_pretrained("paragon-analytics/ADRv1")
 
 def adr_predict(x):
     encoded_input = tokenizer(x, return_tensors='pt')
@@ -18,3 +29,4 @@ def adr_predict(x):
 sentence = "I have severe pain."
 
 adr_predict(sentence)
+```