Update README.md

README.md

@@ -6,16 +6,22 @@ pipeline_tag: fill-mask
 tags:
 - biology
 - medical
+- veterinary
+- clinical
 widget:
-- text: "poc all well. wound healed. No [MASK] on exam. Microchip working.  Sign off, resee if worried."
-  example_title: "Post operative Checkup"
-- text: "other 2 degu's unwell recently want health check for this one appears well for age blood [MASK] 3.8. offer to reweigh and monitor weight"
-  example_title: "Blood Glucose check"
+- text: >-
+    poc all well. wound healed. No [MASK] on exam. Microchip working.  Sign off,
+    resee if worried.
+  example_title: Post operative Checkup
+- text: >-
+    other 2 degu's unwell recently want health check for this one appears well
+    for age blood [MASK] 3.8. offer to reweigh and monitor weight
+  example_title: Blood Glucose check
+base_model:
+- google-bert/bert-base-uncased
 ---
 
 
-
-
 # PetBERT
 
 PetBERT is a masked language model based on the BERT architecture further trained on over 500 million additional words from first-opinion veterinary clinicians from across the UK
@@ -42,7 +48,7 @@ from transformers import AutoTokenizer, AutoModelForMaskedLM
 tokenizer = AutoTokenizer.from_pretrained("SAVSNET/PetBERT")
 model = AutoModelForMaskedLM.from_pretrained("SAVSNET/PetBERT")
 
-PetBERT_masked = pipeline("fill-mask", model=model, tokenizer=tokenizer)
+PetBERT = pipeline("fill-mask", model=model, tokenizer=tokenizer)
 PetBERT('Suspected pneuomina, will require an [MASK] but in the meantime will prescribed antibiotics')
   
 ```
@@ -123,5 +129,4 @@ Adaption of the ULMFiT framework was utilised in the production of ‘PetBERT’
 This work would not have been possible without the contribution of practicing vets across the UK contributing to the SAVSNET project and without the help and support of the SAVSNET core team comprising Bethaney Brant, Steve Smyth and Gina Pinchbeck. 
 
 
-![alt text](Screenshot%20from%202023-12-13%2012-01-53.png)
-
+![alt text](Screenshot%20from%202023-12-13%2012-01-53.png)