Update README.md

README.md

@@ -52,6 +52,23 @@ We would like to take this opportunity to thank
   - BAD: あなたは○○ができます
   - GOOD: あなたは○○をします
 
+## Performing inference
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("Local-Novel-LLM-project/Ninja-v1-128k", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("Local-Novel-LLM-project/Ninja-v1-128k")
+
+prompt = "Once upon a time,"
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+output = model.generate(input_ids, max_length=100, do_sample=True)
+generated_text = tokenizer.decode(output)
+
+print(generated_text)
+````
+
 ## Merge recipe
   
   
@@ -60,5 +77,8 @@ We would like to take this opportunity to thank
   - VT0.2on0.1 = VT0.1 + VT0.2
   
   - VT1 = all VT Series + Lora + Ninja 128k and Normal
+
 ## Other points to keep in mind
-  If possible, we recommend inferring with llamacpp rather than Transformers.
+- The training data may be biased. Be careful with the generated sentences.
+- Memory usage may be large for long inferences.
+- If possible, we recommend inferring with llamacpp rather than Transformers.