Update README.md

README.md

@@ -31,12 +31,12 @@ This model is a binary classifier that determines whether a sentence is a statem
 - This model consists of a linear classification head on top of BioMedBERT, which is a BERT-based encoder (110 million parameters, 12 layers, 768 hidden).
 - All layers besides 10, 11, and 12, the pooler, and classificaton head were frozen to reduce overfitting on the small training set.
 
-- **Developed by:** [Nathan Gelfand, Darya Shlyk]
-- **Funded by [optional]:** [Larry Hunter]
-- **Model type:** [Supervised fine-tune of a transformer-encoder for text classification]
-- **Language(s) (NLP):** [English]
-- **License:** [MIT]
-- **Finetuned from model [optional]:** [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract]
+- **Developed by:** Nathan Gelfand, Darya Shlyk
+- **Funded by:** Larry Hunter
+- **Model type:** Supervised fine-tune of a transformer-encoder for text classification
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Finetuned from model:** microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
 
 ### Model Sources [optional]
 
@@ -54,12 +54,7 @@ This model is a binary classifier that determines whether a sentence is a statem
 A statement of ignorance, or knowledge gap statement, is a piece of text indicating a lack of knoweldge on some subject. 
 In the field of biomedical research, knowledge gap statements often indicate unanswered questions, which can be useful for researchers 
 looking for new topics of study. We built this sentence-level binary classifier so that  researchers could parse through biomedical papers
-and identify research directives. 
-
-
-in PubMed research papers. 
-
-[More Information Needed]
+to identify research directives. 
 
 ### Downstream Use [optional]
 
@@ -77,7 +72,10 @@ in PubMed research papers.
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+This model was trained on a dataset of 937 annotated statements from articles about monogenic epilepsies. Due to the small dataset size, it is possible that
+the classifier will perform better on statements related to monogenic epilepsies. 
+
+The statements 
 
 ### Recommendations
 
@@ -89,7 +87,18 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 Use the code below to get started with the model.
 
-[More Information Needed]
+```python
+!pip install transformers 
+from transformers import pipeline
+
+classifier = pipeline("text-classification",model="hunter-lab/sentence-level-ignorance-classifier")
+
+sentence = "Consequently, there is a pressing need to enhance basic mechanistic and clinical studies, with a focus on individual differences, to advance the exploration of BCAAs in treating neurological disorders and to provide more robust evidence supporting their clinical applications."
+
+result = classifier(sentence)
+
+print(result)
+```
 
 ## Training Details