Update README.md

README.md

@@ -13,6 +13,8 @@ to predict the sentiment and subject of an article
 
 ## How to Use
 
+Load the model:
+
 ```py
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
@@ -38,3 +40,39 @@ pipe = pipeline(
     return_full_text=False,
 )
 ```
+
+Prompt format:
+
+```py
+prompt = """
+### Title:
+<YOUR ARTICLE TITLE>
+### Text:
+<YOUR ARTICLE PARAGRAPH>
+### Prediction:
+""".strip()
+```
+
+Here's an example:
+
+```py
+prompt = """
+### Title:
+Bitcoin Price Prediction as BTC Breaks Through $27,000 Barrier Here are Price Levels to Watch
+### Text:
+Bitcoin, the world's largest cryptocurrency by market capitalization, has been making headlines recently as it broke through the $27,000 barrier for the first time. This surge in price has reignited speculation about where Bitcoin is headed next, with many analysts and investors offering their predictions.
+### Prediction:
+""".strip()
+```
+
+Get a prediction:
+
+```py
+outputs = pipe(prompt)
+print(outputs[0]["generated_text"].strip())
+```
+
+```md
+subject: bitcoin
+sentiment: positive
+```