Update README.md

README.md

@@ -1,3 +1,48 @@
----
-license: apache-2.0
----
+# Usage
+
+```python
+from transformers import BertTokenizer, BertForSequenceClassification
+import numpy as np
+
+finbert = BertForSequenceClassification.from_pretrained('yiyanghkust/finbert-tone',num_labels=3)
+tokenizer = BertTokenizer.from_pretrained('yiyanghkust/finbert-tone')
+
+sentences = ["there is a shortage of capital, and we need extra financing", 
+             "growth is strong and we have plenty of liquidity", 
+             "there are doubts about our finances", 
+             "profits are flat"]
+
+inputs = tokenizer(sentences, return_tensors="pt", padding=True)
+outputs = finbert(**inputs)[0]
+
+labels = {0:'neutral', 1:'positive',2:'negative'}
+for idx, sent in enumerate(sentences):
+    print(sent, '----', labels[np.argmax(outputs.detach().numpy()[idx])])
+    
+'''
+there is a shortage of capital, and we need extra financing ---- negative
+growth is strong and we have plenty of liquidity ---- positive
+there are doubts about our finances ---- negative
+profits are flat ---- neutral
+'''
+
+```
+
+# Cite
+
+```latex
+@misc{yang2020finbert,
+    title={FinBERT: A Pretrained Language Model for Financial Communications},
+    author={Yi Yang and Mark Christopher Siy UY and Allen Huang},
+    year={2020},
+    eprint={2006.08097},
+    archivePrefix={arXiv},
+    }
+
+```
+
+# License
+
+---
+license: apache-2.0
+---