Update README.md

README.md

@@ -26,7 +26,9 @@ pip3 install -U mtkresearch
 
 ```python
 from transformers import AutoModel, AutoTokenizer
+from transformers import GenerationConfig
 import torch
+from mtkresearch.llm.prompt import MRPromptV3
 
 model_id = 'MediaTek-Research/Breeze2-8B-Instruct-v0_1'
 model = AutoModel.from_pretrained(
@@ -35,11 +37,37 @@ model = AutoModel.from_pretrained(
     low_cpu_mem_usage=True,
     trust_remote_code=True,
     device_map='auto').eval()
+
 tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, use_fast=False)
+
+generation_config = GenerationConfig(max_new_tokens=2048, do_sample=False, repetition_penalty=1.1)
+
+prompt_engine = MRPromptV3()
+
+sys_prompt = 'You are a helpful AI assistant built by MediaTek Research. The user you are helping speaks Traditional Chinese and comes from Taiwan.'
+
+def _inference(prompt, tokenizer, model, generation_config):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    output_tensors = model.generate(**inputs, generation_config=generation_config)
+    output_str = tokenizer.decode(output_tensors[0])
+    return output_str
 ```
 
 ## Feature: Instruction Following
 
+```python
+conversations = [
+    {"role": "system", "content": sys_prompt},
+    {"role": "user", "content": "請問什麼是深度學習？"},
+]
+
+prompt = prompt_engine.get_prompt(conversations)
+output_str = _inference(prompt, tokenizer, model, generation_config)
+result = prompt_engine.parse_generated_str(output_str)
+print(result)
+# {'role': 'assistant', 'content': '深度學習是一種人工智慧技術，主要是透過模仿生物神經網路的結構和功能來實現。它利用大量數據進行訓練，以建立複雜的模型並使其能夠自主學習、預測或分類輸入資料。\n\n在深度學習中，通常使用多層的神經網路，每一層都包含許多相互連接的節點（稱為神經元）。這些神經元可以處理不同特徵的輸入資料，並將結果傳遞給下一層的神經元。隨著資料流向更高層次，這個過程逐漸捕捉到更抽象的概念或模式。\n\n深度學習已被廣泛應用於各種領域，如圖像識別、自然語言處理、語音識別以及遊戲等。它提供了比傳統機器學習方法更好的表現，因為它能夠從複雜且非線性的數據中提取出有用的資訊。'}
+```
+
 ## Feature: Visual Instruction Following
 
 ## Feature: Function Calling