Update README.md

README.md

@@ -15,12 +15,21 @@ A fine-tuned model for fact-classification task on English tweets about COVID-19
 ## Intended uses & limitations
 
 #### How to use
-
+Load pipeline
 ```python
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-tokenizer = AutoTokenizer.from_pretrained("ans/vaccinating-covid-tweets")
-model = AutoModelForSequenceClassification.from_pretrained("ans/vaccinating-covid-tweets")
+from transformers import pipeline
+pipe = pipeline("sentiment-analysis", model = "ans/vaccinating-covid-tweets")
+seq = 'The Pfizer-BioNTech COVID-19 vaccine is authorized for use under an Emergency Use Authorization (EUA) for active immunization to prevent COVID-19 caused by SARS-CoV-2 in individuals 16 years of age and older'
+
+pipe(seq)
+```
+
+Expected output
+```
+seq = "There is no FDA-approved vaccine to prevent COVID-19."
+pipe(seq)
 ```
+[{'label': 'true', 'score': 0.9996959567070007}]
 
 #### Limitations and bias
 
@@ -61,5 +70,4 @@ Provide examples of latent issues and potential remediations.
   - Team members: Ahn, Hyunju; An, Jiyong; An, Seungchan; Jeong, Seokho; Kim, Jungmin; Kim, Sangbeom
   - Advisor: Prof. Wen-Syan Li
 
-# ![GSDS](https://gsds.snu.ac.kr/sites/gsds.snu.ac.kr/files/GSDS_logo.png)
 <img src="https://gsds.snu.ac.kr/sites/gsds.snu.ac.kr/files/GSDS_logo.png" width="300" height="100">