Update chat template for RakutenAI-7B-Chat model

Added custom chat template for RakutenAI-7B-Chat. It allows user to use "tokenizer.apply_chat_template()" function to convert input chat data into required format. Please go through the example provided in ReadME file for more detail.

README.md

@@ -16,6 +16,37 @@ An independent evaluation by Kamata et.al. for [Nejumi LLMリーダーボード
 ## Usage
 
 ```python
+
+# With RakutenAI-7B-Chat's custom chat template.
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = "Rakuten/RakutenAI-7B-chat"
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype="auto", device_map="auto")
+model.eval()
+
+chat = [
+	
+	{"role": "system", "content": "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions."},
+	{"role": "user", "content": "How to make an authentic Spanish Omelette?"},
+]
+
+input_ids = tokenizer.apply_chat_template(chat, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(device=model.device)
+tokens = model.generate(
+    input_ids,
+    max_length=4096,
+    do_sample=False,
+    num_beams=1,
+    pad_token_id=tokenizer.eos_token_id,
+)
+out = tokenizer.decode(tokens[0][len(input_ids[0]):], skip_special_tokens=True)
+print("ASSISTANT:\n" + out)
+print()
+
+
+# Without using custom chat template.
+
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 model_path = "Rakuten/RakutenAI-7B-chat"