Update README.md

README.md

@@ -29,6 +29,29 @@ Fin-RWKV is a cutting-edge, attention-free model designed specifically for finan
 - Finance-Specific Training: Trained on the gbharti/finance-alpaca dataset, ensuring that the model is finely tuned for financial data analysis.
 - Transformers Library Integration: Built on the popular 'transformers' library, ensuring easy integration with existing ML pipelines and applications.
 
+## How to use
+```py
+from transformers import AutoTokenizer, AutoModelForCausalLM, StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer
+from threading import Thread
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("umuthopeyildirim/fin-rwkv-1b5")
+model = AutoModelForCausalLM.from_pretrained("umuthopeyildirim/fin-rwkv-1b5")
+
+prompt = "user: Is this headline positive or negative? Headline: Australian Tycoon Forrest Shuts Nickel Mines After Prices Crash\nbot:"
+
+# Tokenize the input
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+# Generate a response
+output = model.generate(input_ids, max_length=333, num_return_sequences=1)
+
+# Decode the output
+generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+print(generated_text)
+```
+
 ## Competing Against
 | Name          | Param Count | Cost | Inference Cost |
 |---------------|-------------|------|----------------|